Inventory Control at Bolletje Almelo.

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(1)Inventory Control at Bolletje Almelo. I want Bolletje biscuit rusk….but not on stock.. University of Groningen Faculty of Economics and Business MSc Technology Management. Concept Thesis Diagnoses Research Project. Supervisors University of Groningen dr. J. Riezebos dr. N.D. van Foreest. Supervisor Bolletje Almelo H. Verduyn. Author F.M. Klein Entink July 2009.

(2) Management Summary This master thesis deals with the topic of inventory control and concerns a case study at Bolletje B.V. in Almelo. Bolletje B.V. is preparing for a reorganization of her production facilities in Almelo. This reorganization, called the master plan, concerns primarily the replacement and extension of current biscuit rusk and knackebröd production facilities. The problem for Bolletje concerns the reduced storage capacity after a future implementation of this master plan. Warehouse capacity available for the storage of finished goods will be reduced by 2000 pallet places on estimation. In light of this problem the research goal was stated as follows: ‘To develop (a) Production Planning and Control (PPC)/Invenory Control (IC) method(s) that will make it possible for Bolletje to work with less inventory and reduce inventory costs.’ Subsequently, the focus of the research was limited to Finished Goods Inventory (FGI) of biscuit rusk articles. A diagnosis of current practice at Bolletje showed that current IC policy consists of maintaining arbitrary inventory levels, usually equal to two weeks of sales. This is not really a policy of controlling inventory taking into account sales, planning and production targets, but rather a way of using inventory to reach targets with the greatest amount of flexibility and security. It is clear that the costs of holding inventory nor the costs of setups in production are taken into account. For Bolletje costs of holding inventory relevant for IC decision making would include capital costs, risk of obsolescence and handling. After a literature review on the topic of IC a model was developed for Bolletje which determines optimal production frequencies based on a minimization objective on the total costs of ordering and holding an item in inventory. The model included only a few relevant production frequencies and was linked with an IC method that fixes the ordering frequency but orders a variable production quantity up to a fixed level. At the same time it was determined that daily production would allow for make-toorder (MTO) production. The ‘every day’ production frequency therefore had a total cost function that only included setup costs. The model was applied to Bolletje’s current portfolio of make-to-stock (MTS) items of biscuit rusk products. In this application regard was given to assumptions about the master plan situation. The results showed that the average inventory level of biscuit rusk articles could be reduced from 1120 to 320. This will provide a significant step towards the needed reduction of 2000 pallet places based on current storage practice. Bolletje can reach such a result by producing items with stable daily demand on order and producing other items only once per week or once per two weeks. Implications for planning were discussed and it was recommended to give first priority to daily MTO production, next to production of MTO items and last to production of MTS items. 2.

(3) Preface With this thesis I conclude my master Technology Management at the University of Groningen. I would like to thank Bolletje Almelo for providing the opportunity to perform my research at this company. I experienced a very open and friendly culture at Bolletje since people always allowed me to have a look at their daily work and ask questions. I would like to thank all my colleagues of the logistical and purchasing department who helped me with my research but also with having a great time at Bolletje. Especially I would like to thank my supervisor at Bolletje, Hans Verduyn for his support, feedback and nice conversations in our weekly meetings. Furthermore, I would like to thank my first supervisor dr. Jan Riezebos for introducing the idea of contacting Bolletje Almelo in the first place. During the research, his feedback and helpful suggestions led me to the completion of the research and the thesis. I would like to thank my second supervisor, dr. Nicky van Foreest, for providing feedback on my concept thesis and reviewing my final thesis.. Finally I would like to thank my family, and my girlfriend specifically, for their support. Special thanks goes out to my brother for providing a place to live in Enschede and for his critique on my thesis.. 3.

(4) List of abbreviations CU = Consumer Units CV = Coefficient of Variation (SD/Mean) FGI = Finished Goods Inventory KPI = Key Performance Indicator MPS = Master Production Schedule MTO = Make-to-order MTS = Make-to-stock PLC = Product Life Cycle RMI = Raw Material Inventory SCM = Supply Chain Management SD = Standard Deviation SKU = Stock Keeping unit (is the same as a MTS article) Introduction of important definitions Colli = boxes/packages containing a certain number of consumer units. A pallet contains a fixed number of colli which is different for each article. The same goes for the number of CU per box. Net. Norm output = the production rate (in consumer units or recalculated as colli) produced under normal conditions, adapted for an article specific product loss and line disruption percentage.. 4.

(5) Table of contents Management Summary............................................................................................................................ 2 Preface ..................................................................................................................................................... 3 List of abbreviations ................................................................................................................................ 4 1. Introduction: The problem situation and its context at Bolletje B.V................................................... 7 1.1 Problem Description ...................................................................................................................... 7 1.2 Introduction to Bolletje B.V. ......................................................................................................... 8 1.3 Production process characterization of biscuit rusk production .................................................. 11 1.4 Current production practice ......................................................................................................... 12 1.5 Current production planning practice .......................................................................................... 14 2. Research Design ................................................................................................................................ 15 2.1 Area of concern ........................................................................................................................... 15 2.2 Framework of ideas ..................................................................................................................... 16 2.3 Methodology ............................................................................................................................... 19 2.4 Summary of research design. ...................................................................................................... 20 3. Current IC practice at Bolletje........................................................................................................... 21 3.1 IC at Bolletje ............................................................................................................................... 21 3.2 Costs of holding inventory for Bolletje ....................................................................................... 21 3.3 FGI: Inventory level and value for biscuit rusk........................................................................... 23 3.4 Conclusion ................................................................................................................................... 25 4. Literature review: existing concepts and models for inventory control. ........................................... 26 4.1 Inventory control through order policies ..................................................................................... 26 4.2 Deterministic models ................................................................................................................... 26 4.3 Stochastic models ........................................................................................................................ 27 4.4 MTO/MTS decision .................................................................................................................... 29 4.5 Conclusion ................................................................................................................................... 29 5. The master plan situation described. ................................................................................................. 30 5.1 Internal and external storage ....................................................................................................... 30 5.2 Biscuit rusk production: Current design knowledge and assumptions ........................................ 35 6. Inventory Control: A total cost model for the master plan situation ................................................ 37 6.1 Determining model requirements and parameters ....................................................................... 37 6.2 Determining relevant production frequencies for Bolletje. ......................................................... 39 6.3 Adding the MTO/MTS decision to the model ............................................................................. 40 6.4 Determining the IC Method for MTS items ................................................................................ 40 5.

(6) 6.5 Definition of the total cost functions per production frequency .................................................. 41 6.6 Including external storage costs in the model ............................................................................. 44 7. The application of the cost model ..................................................................................................... 45 7.1 The results: Optimal production frequencies............................................................................... 45 7.2 Results: Inventory reductions ...................................................................................................... 46 7.3 Results of external cost evaluations ............................................................................................ 46 7.4 Additional revisions of the results. .............................................................................................. 50 7.5 Conclusion. .................................................................................................................................. 50 8. Application of the IC policies in production planning ...................................................................... 52 8.1 The new planning and scheduling situation ................................................................................ 52 8.2 Simulation of the new policies in detail planning ....................................................................... 52 8.3 Conclusions drawn from simulation results. ............................................................................... 57 8.4 Recommendations for scheduling problems. .............................................................................. 58 8.5 Supply chain optimization for inventory control......................................................................... 60 9. Discussion ......................................................................................................................................... 61 References ............................................................................................................................................. 63 Appendix A. Process scheme of biscuit rusk production ...................................................................... 65 Appendix B. Calculation of pallet places in Master Plan ...................................................................... 66 Appendix C. Week demand volumes and variability based on data set 1. ............................................ 67 Appendix D. Indication of inventory holding costs per year for Bolletje ............................................. 69 Appendix E. Input data for Total Cost Model ....................................................................................... 70. 6.

(7) 1. Introduction: The problem situation and its context at Bolletje B.V. Bolletje B.V. is in the process of reorganizing her production facilities in Almelo. A key aspect concerns its inventory control. Warehouse capacity will be cut to improve and extend production. Bolletje aims to obtain a significant reduction in inventory in order to execute the reorganization and to cut inventory holding costs. This thesis evaluates some methods to reach that goal and discusses their implications for planning and production. In this chapter the problem situation will be introduced in more detail followed by an introduction of the company Bolletje B.V. and a description of several aspects of the system under research.. 1.1 Problem Description The reason for this research to be carried out is related to a future situation currently under research at Bolletje. It concerns the so-called master plan. Management of Bolletje is determined to replace and extend current capacity for production of biscuit rusk and knackebröd while at the same time changing the layout and allocation of its production lines at its production locations in Almelo and Heerde. The goal is, besides extending capacity, to increase production and cost efficiencies by further automation and improved line design, while also improving material handling in terms of easiness and intensity. By the end of 2010 the existing three biscuit rusk lines (and the even older two biscuit rusk lines, of which one is already out of operation) will be replaced by two ‘state-of-the art’ production lines. At this moment one Production Building (16) is to a large extent used for product storage, but in 2010 the two new production lines for biscuit rusk will be allocated to this building. The biscuit rusk lines which are currently still in operation will be dismantled and the free space will be used for one and probably two new gingerbread production lines. These gingerbread lines will replace one old line at the production location in Heerde and another line at Almelo. All old lines up for replacement will be replaced gradually. Generally, they will not be dismantled before the new lines are running smoothly. Besides the introduction of new lines the allocation of current knackebröd lines is important as well. Knackebröd and biscuit rusk generally use the same raw materials, have similar production methods and are therefore preferably placed close together in the same production environment. The idea is that these products can, to a certain extent, use the same raw material inventories (RMI, stored mostly in silo’s) and can make use of the same dough producing room. The implication will be that in 2010 at least one and maybe two new knackebröd production lines will be introduced in Building 16 in Almelo replacing one old line in Heerde. One line currently operating in Almelo will remain in production. The problem for Bolletje lies in the limited space available for inventory storage in the future as the knackebröd and biscuit rusk production lines will take most floor space of building 16 as well as a part of the adjacent warehouse. Floor space that will come available for storage in the master plan has 7.

(8) limited opportunity for piling up inventories as well. Therefore, management of Bolletje wants to look for production planning and control methods to work with smaller inventories and with lower inventory costs. Warehouse capacity will be reduced with approximately 2000 pallet places after execution of the master plan. If the building currently used for biscuit rusk production would be temporarily put to use as storage space then only 900 pallet places might be lost. But on a longer term this building will be removed completely to use the created space for expansion. On the next two pages the layout of the current situation (Figure 1) and the master plan situation (Figure 2) are presented. The red area’s give a rough indication of storage space. Other implications stemming from the master plan which are relevant for this research will be discussed later in this thesis. In the next chapter the goal of this research and the research approach will be explained in relation to the above problem situation. First more will be told about the company Bolletje B.V. and processes related to the problem situation.. 1.2 Introduction to Bolletje B.V. Bolletje has been a family company owned by the family Ter Beek ever since 1867. At first it started as a bakery and shop in Almelo. Since 1954 Bolletje changed towards an industrial producer of biscuit rusk as the company moved to its current location at the Turfkade in Almelo. Over the following years the strategy was to increase the product portfolio towards the complete ‘bread-replacement product market’ while increasing the market share with takeovers of other players in the market. Bolletje is mainly a national player on this market but also does export of some of her products accounting for approximately 25 % of sales. Plans for the future are also aiming for a more significant role in the European market. The current product portfolio consists of the following product families: -. Biscuit rusk/Rusk/Crispbakes (in Dutch: ‘beschuit’) and Knackebröd. -. Rye Bread/Black bread (in Dutch: ‘roggebrood’) and Special Bread;. -. Honey Cake/Gingerbread; (in Dutch: ‘ontbijtkoek’) and Biscuits and Cookies;. -. Bread additions/ sandwich filling (in Dutch: ‘broodbeleg’) and Pita & Bagels;. -. and Salty sticks/Salt wafers (in Dutch: ‘pepsels’);. -. Seasonal (December) products; (Dutch names: ‘kruidnoten en taai-taai’);. These products are produced at three production locations in Almelo, Heerde and Amsterdam. In Amsterdam Pita and Bagel products are produced while Heerde focuses on Gingerbread/Cake, biscuits and knackebröd. In Almelo, where the head office is located (see Figure 1), most production takes place including the typical product for Bolletje: biscuit rusk. Other products produced in Almelo are knackebröd, ginger bread, bread, salt wafers and seasonal products. 8.

(9) Figure 1. Current Layout with red marked area's indicating space for inventory storage. 9.

(10) Figure 2. Master Plan Layout with red marked area's indicating space for inventory storage. 10.

(11) 1.3 Production process characterization of biscuit rusk production With Bolletje’s product portfolio and production processes it typically belongs to the food processing industry. Further, Van Donk (2001) makes a distinction between companies that produce intermediate products from natural materials and companies that produce consumer products from natural materials and intermediate products. Bolletje belongs to the latter. For an extensive characterization and discussion of the food processing industry is referred to articles by van Donk (2001) and a recent book by Entrup (2005, chapter 3). Van Donk (2001) & Akkerman and van Donk (2007) recognize that the food processing industry is generally characterized by a two-stage process consisting of processing of raw materials and packaging. Usually these two stages are separated by an inventory of intermediate products. But this is not the case for the production of biscuit rusk at Bolletje. The products are produced on continuous conveyor belt lines without a decoupling point between the processing stage and the packaging stage. The difference is shown in Figure 3 below.. Figure 3. Top: typical two-stage food processing, Bottom: Bolletje’s single-stage production. The production process of biscuit rusk production consist of 4 main processes: dough forming, dough rising, baking and packaging. Biscuit rusk production has two stages of baking because in the first oven a dough unit containing material for 2 biscuits is baked, and afterwards two halves are cut. These separate halves are then baked for the second time (coloring), to produce the final products. A more extensive process scheme of biscuit rusk production is presented in Appendix A. For biscuit rusk the standard (natural) dough is processed and supplied to the line continuously. For recipes that need additional ingredients the dough is first supplied to large containers for additional processing. The automated conveyor belt line takes batches of dough units through the same sequence of processing stations until the end of the first baking process. After that, products are again moved by the conveyor belt but now as discrete products until they are sorted out as batches for the packaging stage. All operations have the same constant operating time except for different recipes/products. Given batch wise production for recipes with additional ingredients production would qualify as disconnected line flow according to the process typologies introduced by Rutten (1995). Rutten’s 11.

(12) typologies (1995) are presented as the y-axis in a matrix drawn up by Entrup (2005) shown in Figure 4 below. New production lines are designed to have a continuous dough forming machine for all recipes and products. Therefore, in the future the production process will be adequately characterized as single stage process with connected line flow.. Figure 4. Product-process matrix (Entrup, 2005). According to Entrup (2005) the fresh food industry is usually situated in the grey shaded area in Figure 4. Concerning the product structure the biscuit rusk products would be somewhere along the continuum with large quantities of commodity products being produced but frequently out of customized recipes. Therefore, they would indeed fit in the grey area. One character related to the production lines is the wide variety of product types (sizes and recipes) that is produced. This can be linked to recent trends of product differentiation in fresh food industries (Entrup, 2005: page 51).. 1.4 Current production practice Biscuit rusk is produced on three roughly similar parallel production lines. All production lines are in use for 25 years or longer. Line disruptions and product loss are currently a major problem for Bolletje. Small interruptions are experienced regularly because of the ‘degraded current state’ of the lines. The old production lines were originally designed to produce a limited number of similar products (one basic recipe and biscuit rusk size). But in the current situation Bolletje has a wide variety of recipes and a few different product sizes which presents one of the causes of problems in process control and stability. The production manager simply stated that ‘the production process is not well controlled.’ One example of this was easily identified as the positioning of dough units into biscuit rusk moulds results in a few ‘misfits’ almost every batch. Other production problems were easily identified just by attending daily morning meetings between the detail planner and production foremen. In these meetings the output and problems of the previous day are discussed. Many times, production had lost ‘half an hour of production in one order’ and ‘an hour in another’ because of disruptions in the line. Usually it was concluded that the cause was a dysfunction of one of the machines but that it had been fixed. Yet, the next time a disruption would occur somewhere else. Sometimes adequate reaction of line employees seemed lacking or raw materials were sometimes lacking. Overall can be concluded that small interruptions occur regularly. 12.

(13) Product loss is another form of waste in production and is a source of variable output. Products which are visually inspected and found ‘not according to standard’ are removed. When a major interruption occurs all the product inside the oven is removed and crunched. The crunched material is sold as ‘paneermeel’ or sold to be used as an ingredient of animal feeding material. A final issue concerning the current production process is the need for changeovers. Changeovers or setups at Bolletje are very typical for the food processing industry. Van Dam (1995) differentiates three changeover types in the Process Industry as mentioned by Entrup (2005, p 62): •. Format change: change of size of packaging material;. •. Product change: change of unpacked product, frequently related with cleaning;. •. End product change: change of the packaging material specific to the order, neither change of size nor change of unpacked product required.. Changeovers in biscuit rusk production include adjustments of ovens for different recipes and changing of packaging material for different articles. What van Dam (1995) calls a ‘Format change’ sometimes occurs when different multiples of consumer units (CU) of the same biscuit rusk are packaged together . Most times though, changes of packaging material are order related (i.e. End product changes) and go together with a change of the unpacked product as well. These changeovers take approximately 10 minutes. Van Dam’s changeover type ‘Format change’ can for Bolletje’s case also be identified as a changeover for different biscuit rusk sizes. When a changeover occurs between products with different biscuit sizes, the moulds and the plates carrying the moulds have to be replaced. A changeover like this takes approximately 2,5 hours. First, after finishing production, employees remove all the plates in about 1 hour. Then the new plates are inserted on the line and several settings will have to be adjusted for the new product (for instance oven temperature). If no major disruptions take place in the line (production will start up during the last part of the changeover) this will take around 1,5 hours. Biscuit sizes can differ in height (Low and High biscuit rusk) and width (Twents Biscuit rusk articles only). It is clear that ‘end product changes’ and ‘product changes’ as identified by van Dam (1995) usually go together for Bolletje and there is one typical example of van Dam’s ‘product change’. Production of 10-seeds biscuit rusk will soil the production line to such an extent that it has to be cleaned afterwards. Also, this product requires an additional machine to be installed on the line before production starts and it has to be removed from the line afterwards. Therefore, production of this article will always be scheduled in the end of the week so that during cleanup on Saturday no regular production time is used.. 13.

(14) 1.5 Current production planning practice Bolletje works with a planning hierarchy established in 2008 consisting of an yearly sales estimate, a production year plan, a Master production schedule (MPS) and a detail plan. The MPS is established by the MPS-planner based on inventory levels at the end of the current week, minimum stock levels and sales estimates for the upcoming weeks. When the MPS is fixed the Detail Planner will prepare a Detail Plan on Thursday for the upcoming week. He uses the fixed plan from the MPS and the production hours needed are calculated based on the net norm output per article. He determines a day-to-day planning based on experience and personal knowledge about what is practical and efficient for production taking into account setup times. This means that the detail planner tries to limit changeovers between different sizes of biscuit rusk. Usually the planner tries to stabilize production by performing long runs of a few products with similar recipes and size. It also means that products with high and stable demand volumes per week are used by the detail planner for ‘flexible scheduling’. That means that these products are sometimes not produced in a week with high overall demand as to fulfill demand for items prone to higher demand variability. Also when unexpected downtime, unexpected short term orders, or short term adjusted demand estimates occur, planned production for such items is usually the first to be adjusted as to make room for the more critical items at that moment. Then, a few days later inventory is replenished by a large run of more than 2 shifts (16 production hours). Every morning the Detail Planner discusses the production performance of last day with the production foremen and maintenance crew. When no severe disruptions occurred he will print production orders for the next day and provide them to the production departments. In case of severe disruptions either the detail plan will have to be adjusted or the missed output is caught by inventory for the time being. Usually this means that missed production will have to be filled up later as stock levels have to adhere to their minimum of approximately two weeks of demand. In general can be concluded that detail planning and scheduling are performed based on ‘rules of thumb’ known primarily by the detail planner. The urge to schedule long runs in varying frequencies over multiple weeks results in quite high inventory levels for some items. Furthermore the inventory ensures a decoupling of supply and demand adhering to delivery requirements. Bolletje is dealing with so-called ABC delivery as a minimum requirement from the retail market. This means that orders come in before 10 o’clock on day A. Then a plan in the warehouse is prepared for order-picking on day B. Finally on day C the orders are shipped to the customers. The unreliable production output (previous section) together with irregular scheduling of long production runs are causes of the need for inventory of biscuit rusk products at Bolletje. Other, market related, causes are the generally ‘short’ delivery lead time of 2 days and variability and unpredictability of demand. 14.

(15) 2. Research Design To perform a good research a research design is needed as a starting point. Checkland and Holwell (1998) recommend that any research should explain the area of concern (A) it is applied to, the framework of idea’s (F) that will be applied to ‘A’ and the methodology (M) that will be used. In this chapter the research design will be explained in relation to these research elements.. 2.1 Area of concern The problem situation described in section 1.2 directly relates to the areas of Production Planning and Control (PPC) and its subarea of Inventory Control (IC) specifically. Management is looking for new PPC and IC methods which would result in lower inventories. The goal is to decrease the space needed for inventory. Another goal is to bring awareness of costs associated with holding inventories and to reduce these costs. Several restrictions have to be taken into account as well. First, Bolletje has a strong focus on the customer and this is related to delivery reliability or service level. The service level is measured and evaluated as an important Key Performance Indicator (KPI) in the relation between and performance of the planning department and the sales department. A second goal or restriction on recommendations to be made is that Bolletje strives to realize robust planning and production. Finally, the recommendations should have a focus on the future situation being developed in the so-called Master Plan. Thereby, the problem is that this situation is clear only to a small extent currently. Taking all this into account the research goal was Formulated as follows: Research Goal: To develop (a) PPC/IC method(s) that will make it possible for Bolletje to work with less inventory and reduce inventory costs. The methods should ideally ensure that future warehouse space is sufficient for holding inventory and that inventory levels are controlled more tightly over time. At the same time the methods should deal with the following boundary restrictions: o. Service level performance, being the main focus of Bolletje, cannot be decreased.. o. The methods applied should relate to the future situation stemming from the master plan.. Because of the wide overall product portfolio at Bolletje and the differences in production and planning methods the research will be limited to one type of products which will be directly influenced by the master plan and have the highest impact on total inventories. This is the case for biscuit rusk products. Second, inventories can be split up in Raw materials Inventory (RMI), intermediate inventories and Finished goods inventory (FGI). The focus of the research will be on FGI since this 15.

(16) inventory takes the most storage space of total inventory currently. The main area of concern is hereby identified as FGI of biscuit rusk articles. The process in which the FGI serves a purpose for Bolletje is the supply and demand process between Bolletje and its customers and the uncertainty both sides of the process bring. The supply process can be viewed as the production taking place at Bolletje and the field of production planning and control (PPC) is the factor that should regulate this process. Especially of interest will be the field of Inventory Control (IC) but this is regarded as being a part of PPC. The complete picture is presented below in Figure 5. Uncertainty Production characteristics. Uncertainty. Finished goods inventory. Demand characteristics. Production Planning and control characteristics. Figure 5. The Area of concern including FGI, PPC and the supply and demand interaction.. This research will focus on controlling the supply side of finished goods of biscuit rusk in order to reach the research goal. The research question is therefore drawn up as follows: Research question: How should a PPC/IC method control the supply of finished goods in order to reduce inventory and inventory costs?. 2.2 Framework of ideas Now that the area of concern has been identified, a framework of ideas (F) can be presented. Variables influencing FGI have to be identified and a delimitation of variables under research should be made to conclude the framework of ideas. Spearman and Hopp (2008) note that: “If we could ship everything we produced directly to customers there would be no need for FGI.” Zipkin (2000) notes that the main reason for carrying inventory is related to ‘mismatches’ between supply and demand and introduces a list of seven variables: Demand processes: •. Smooth or lumpy demand. •. Variations in demand over time. •. Unpredictable demand variations. Supply processes: •. Economies of scale in supply 16.

(17) •. Capacity limits. •. Delays in response – lead times. •. Imperfect quality. This list basically extents on a similar list introduced by Spearman and Hopp (2008, page 606). PPC is in this research defined by what Bertrand, Wortmann and Wijngaard (1998) call ‘logistical control’ (translated from Dutch): The control of availability and use of materials and capacity sources in time, number and location. In this research Inventory Control (IC) is assumed to be a part of PPC as dealing with an alternate capacity source; inventory. Although the focus lies with IC; it cannot be isolated from production planning. Therefore, PPC can be regarded as the process of dealing with what Zipkin (2000) calls ‘mismatches between supply and demand. In the introduction it was identified that Bolletje tries to generate economies of scale by planning large batches. But it does not take into account actual costs and scheduling of one item can be quite irregular. Zipkin (2000) takes into account such characteristics for the demand side by mentioning demand lumpiness and variability. But he directly relates these characteristics directly to economic efficiency for the supply process by putting them together in one variable: economies of scale. This research will be focused on inventory control policies that determine production quantities and/or frequencies in an economic efficient manner. Still one variable not yet mentioned is very interesting when aiming for inventory reductions. This concerns the possibility to make products to order (MTO) inside a delivery lead-time. Basically MTO production means aligning supply frequencies and quantities with actual demand. This concludes the set of variables taken into account in this research. Possible control variables for Bolletje, thereby adding to Zipkin’s list, are therefore identified as: •. Production quantities. •. Production frequencies. •. MTO production. And these variables relate to economic efficiency though associated cost variables: •. Cost of setups. •. Cost of holding inventory.. The conceptual model presented in Figure 6 on the next page shows the possible control variables in green and variables that are needed as input for IC policies in white. When following the arrows in the conceptual model it becomes clear that the assumption is that IC policies control FGI indirectly by determining production quantities and frequencies. Safety stock is determined based on these variables 17.

(18) to ensure fulfillment of demand against the lowest total costs. A thorough discussion of IC literature will be provided in chapter 4. Not directly shown in the conceptual model are the implications for planning and scheduling. A redesign will be mirrored against current planning and scheduling practice at Bolletje to discuss practical implementation.. Figure 6. Conceptual model with variables under research.. When reflecting on variables mentioned by Zipkin (2000) and Spearman and Hopp (2008) it becomes clear that most variables are not considered in this research. At the demand side supply chain management (SCM) and forecasting could be possible area’s for improvement to the end of FGI reduction. But these area’s are unlikely to provide much room for improvement in Bolletje’s case as they were already researched in the past. Concerning the supply side the reason for neglecting most variables is simple: The research considers an unclear future situation of which supply variables will mainly be determined by the redesign of the new production lines. Design of the master plan situation, including line parameters and internal logistics, is currently under research at Bolletje. To be able to answer the research question this research will deal with several sub questions related to the concepts in the conceptual model. The first two questions are determined to reveal current IC practice at Bolletje as well as to identify cost drivers for holding inventory for Bolletje. 1. How is inventory currently controlled at Bolletje? 2. What are the costs of holding inventory at Bolletje currently?. 18.

(19) Question three relates to identifying well known control methods and models from IC literature through a literature review, making input assumptions for the master plan situation and finally setting an IC method for Bolletje. 3. Which concepts and models to perform inventory control identified in literature can be applied to Bolletje’s case? (literature review) After that the most important part of the research question is answered by the presented new IC policy. Still for practical implementation especially related to planning and scheduling, sub questions 6 and 7 will be important to answer as well. By answering these questions the practical working of the new IC policy will be discussed thereby adding value to the final recommendations made to answer the research question. 4. What will have to change in current production planning practice to apply the new IC policy? 5. What will be required of production (supply) to implement the IC policy? To conclude this section the framework of ideas (F) can be summarized as methods and frameworks from PPC and IC literature which can be applied to the area of concern (A). The conceptual model and sub questions should structure this application.. 2.3 Methodology This research can be typified as a practical focused research. The research aims to support decision making for Bolletje Almelo and is therefore applied to a specific context. Because of the specific context of the research and the limited ability for generalization the type of research applied can be typified as a case study. Furthermore, this research aims to test theory in action and can therefore also be typified as ‘action research’ as introduced by Checkland and Holwell (1998). An important implication of using this type of research is that the researcher should be aware that by studying the system under research the researcher himself will influence and change the system. The researcher must take responsibility for practical outcomes and seek to ensure that these represent perceived improvements in the eyes of the participants. (Checkland and Holwell, 1998). Ellram (1996) describes the case study methodology as: “The case study method generally emphasizes qualitative, in depth study of one or a small number of cases. However, case studies may also gather quantitative data.” Stuart, McCutcheon, Handfield, McLachlin and Samson (2002) introduce a generic five stage research process for case studies in operations management. This process is shown in Figure 7 on the next page.. 19.

(20) Figure 7. The five stage research process model (Stuart et al. 2002). The first two stages, concerning the definition of a research question and instrument development. were already discussed. The research question has to adhere to requirements for the Technology Management master research and therefore concerns a problem situation of the company Bolletje B.V. To bring focus in this research, five sub questions were defined relating to a conceptual model. Stage three and four concern data gathering and data analysis. Ellram (1996) distinguishes case studies by the type of data being gathered and the type(s) of analysis applied in the research. The type of data gathered will concern empirical data from Bolletje and both quantitative and qualitative analysis will be applied to come up with recommendations for Bolletje. A literature review should identify best practice in the field of Inventory Control. The case study character then requires an adaption of theoretical concepts to Bolletje’s specific situation. Qualitative data will be extracted from interviews and direct observations and will be used alongside quantitative data like demand, cost and inventory data. In IC theory it is common to make use of modeling techniques and statistical analysis. This is likely to be needed in this research to aid empirical analysis and to aid implementation of theory in practice. The final methodological concept being applied is the concept of triangulation. Triangulation is the use of different techniques or information sources to study the same phenomenon. (Ellram, 1996) This should provide validity within the case study. Stage 5, dissemination of the results, takes place by writing this thesis and by means of a colloqium at the University of Groningen.. 2.4 Summary of research design. The area of concern (A) has been restricted to FGI of biscuit rusk articles and the associated inventory control and overall production planning and control. A conceptual model was drawn up and research questions were Formulated to support the research goal: To develop PPB/IC methods that will make it possible for Bolletje to work with less inventory and reduce inventory costs. Therefore, the framework of ideas, summarized as methods and frameworks from PPC and IC literature, will be applied to the ‘A’ supported by the presented conceptual model and 5 sub questions. The methodology applied will be a case study, limited to the empirical situation at Bolletje Almelo. Analysis of both qualitative and quantitative data will be used and the concept of triangulation will be applied where possible.. 20.

(21) 3. Current IC practice at Bolletje In this chapter current practice of inventory control at Bolletje will be discussed. Collected data of actual inventory levels will be presented and cost drivers of inventory holding costs will be identified.. 3.1 IC at Bolletje Inventory control at Bolletje is limited to the calculation of minimum stock levels and MPS adjustment for maintaining those minimum stock levels. The main focus is on service level targets of 98,5 %. Bolletje takes the fill rate, the fraction of demand that can be satisfied immediately from stock on hand, as the service level measure. This measure is evaluated every week in a meeting of the Sales and Logistics department. But stock levels are determined mainly by rules of thumb like keeping ‘two demand weeks on stock’ while keeping in mind that a major breakdown might occur in production. Minimum stock levels do not regard demand variability nor are they directly linked with production quantities and frequencies. Next, because inventory usually covers several weeks; the production quantities can be large and production frequencies can be low as to ensure production efficiencies. No regard has been given to inventory holding costs in relation with setup costs nor have possibilities for inventory minimization been researched before. With the new situation in which internal storage space will be restricted this has to change. In general it can be concluded that inventory is not controlled but rather used to ensure a high service level, to provide flexibility for production planning and to cover up for problems in production. New ‘state-of-the-art’ lines will be designed for more automation, short setups and a wide product portfolio. IC policies should make use of these improvements. From a ‘lean manufacturing’ perspective buffering against unplanned production downtime is just another form of waste alike the unplanned downtime itself. Certainly downtime because of setups is another form of waste. While the master plan should aim to improve production reliability alongside economical efficiencies, IC should give attention to the trade-off between setup costs and inventory holding costs. In the following paragraph inventory holding costs are identified and current situation inventories will be presented in section 3.3.. 3.2 Costs of holding inventory for Bolletje To provide more insight in the current and future inventory situation at Bolletje regard has to be given to inventory holding costs. To determine these costs several cost drivers have to be identified. Typical inventory costs include, according to Axsäter (2000): •. Capital costs. •. Material handling. •. Storage 21.

(22) •. Damage and obsolescence. •. Insurance. •. Taxes. Axsäter (2000) further argues that costs that are variable with inventory level should be included in inventory holding costs (sometimes denoted in literature as ‘carrying costs’). He states: “In some situations with owned warehouses, these costs (i.e. storage space) may be essentially fixed. This means that they should not be included in the holding costs”. Although Axsäter does not explain this claim it is understood that fixed costs wouldn’t support decision making on inventory levels. For instance, if a fixed warehouse charge would be spread equally over units of inventory then the holding cost per unit would increase when inventory levels are reduced. This would not provide a realistic picture since the created space might be useful for other profit generating activities on the long-term. Capital costs associated with holding inventory relate to money that is invested in inventory which does not add value to the company. Many companies use debt in combination with issuing shares to finance part of their investments. Then the capital costs associated with holding inventory can simply be determined by charging the inventory value with the weighted average costs of capital (WACC). But Bolletje, being a family owned company with no debt capital being used for financing, has no use of such a concept. Yet, every euro invested in inventory will not generate any return. The opportunity costs of capital then represent the return that could be generated by investing the same euro in a profitable project. Businesswise 10% would be acceptable when a benchmark is used with a well profitable project. Therefore, for this research capital costs are assumed to be 10 % annually. Handling costs are related to transport, piling up and picking of pallets. Note that this concerns only handling activities that are not performed for MTO items. When a MTS pallet is scanned at a production parking lot, the warehouse management system provides an advice on the best storage position based on the best-before-date. It is assumed that transport from and to the storage position is similar to transport directly to a loading dock (which is roughly so in the current case and even more so in the master plan as a storage position directly at the end of the production lines becomes available). But only MTS items are first moved to an empty pallet place in the warehouse where additional handling is needed for inserting and extracting the pallet. Together with the warehouse manager the assumption was made that approximately 5 minutes are spend for these handling activities. Given a wage of warehouse personnel of €24 per hour the handling costs per pallet are determined to be €2,- per pallet. A machine charge for these handling activities is neglected since all forklift trucks currently in use are fully depreciated for more than ten years already. Storage costs are only slightly applicable to Bolletje’s situation since primarily the own warehouse is used. But there is an exception since seasonal products have to be produced from approximately May 22.

(23) through December . These items are sold to retailers in large increasing quantities from September through December. During this ‘season’ Bolletje contracts an external storage provider for handling and storing its seasonal products. In the current situation one could argue to assign these costs only to the seasonal products themselves. But when the master plan is implemented and less storage space will be available these costs are relevant for any inventory policy. Costs of external storage will be discussed further in chapter 5. Regarding the cost factor damage and obsolescence the perishability of goods is an important factor to take into account. This factor is of major influence for doing business in the food processing industry. Every product has a best-before date and the period between production and that date is referred to as the ‘shelf-life’ of a product. In general, biscuit rusk products have a shelf-life of six months. Bolletje is allowed to hold us 1/3 of that time (2 months) so that the retailer can hold the items on stock for another 4 months. With a 2 month shelf-life, inventories of biscuit rusk turn obsolete very rarely. That it still can happen is shown by the fact that two MTS biscuit rusk articles were on stock during the research while the customer refused to buy the items as there was a disagreement about the required quality. Just for such a risk a 2 % damage and obsolescence annual charge will be assumed. This will be charged on inventory value just like capital costs of holding inventory. Insurance is another cost factor applicable to Bolletje’s case. Bolletje applies insurance for inventories, buildings and general resources. At Bolletje the warehouse, a shuttle shelve system and inventories themselves have a significant book value to apply insurance costs to. Still the insurance premium is just a few promille. These costs are insignificant and even for fixed for the warehouse and shuttle system. Therefore, these costs are neglected in IC policies. Tax is paid over real property (like the warehouse) but also represents a fixed cost which is therefore not relevant for inventory decisions. It would become a relevant decision factor when Bolletje wants to decide between building an extra warehouse or hiring extra external storage space. The same goes for depreciation in such a situation. Still such a choice is not in place currently.. 3.3 FGI: Inventory level and value for biscuit rusk Inventory levels of biscuit rusk were monitored from week 11 through 26 in 2009. Unit prices were gathered, and the average inventory value was calculated. The result is shown in Table 1. The first column shows the article numbers and description in Dutch while the second column shows the unit price per box. It has to be mentioned that boxes can contain a different number of CU for each article. Also the loading of boxes on a pallet can differ among articles. This is taken into account when measuring average inventory levels in pallets (column 3), in boxes (column 4) and in CU (column 5). The unit price is used to determine the value of the average inventory level in the last column. Only MTS articles are listed in the Table. Still, during the monitoring period there were always some MTO 23.

(24) products on stock, though usually for small periods only. This seems a bit strange as products that are made-to-order are normally not stored in the warehouse. MTO items concern primarily export items which have delivery lead-times of 1 or 2 weeks opposed to two days for other articles. Production of these MTO items is currently not aligned with the transport date resulting in the inventory of MTO articles. On every day that inventory levels were extracted from Bolletjes’ IT system, MTO inventory was such that over the whole data set the average MTO inventory was 120 pallets on a total of 1225.. Biscuit Rusk SKU's inventory 1 SubTotaal Artikel 50-001003 ECHTE BESCHUIT 48 R 2 SubTotaal Artikel 50-001001 ECHTE BESCHUIT 24 R 3 SubTotaal Artikel 50-000485 BESCHUIT AH NATUREL 24 RL 4 SubTotaal Artikel 50-003344 BESCHUIT VOLK VAROPA 80 R 5 SubTotaal Artikel 50-004111 BESCHUIT VOLKOREN 24 RL 6 SubTotaal Artikel 50-010021 BESCHUIT TWENTSCHE 12 R 7 SubTotaal Artikel 50-007221 BESCH 10 ZADEN 13 ST 8 SubTotaal Artikel 50-004101 BESCHUIT VOLKOREN 12 RL 9 SubTotaal Artikel 50-005111 BESCH MEERGRANEN 13 ST 10 SubTotaal Artikel 50-000501 C1000 NATUREL BESCH 24 RL 11 SubTotaal Artikel 50-003518 C1000 VOLK. BESCHUIT24 RL 12 SubTotaal Artikel 50-001022 ECHTE BESCHUIT A 24X2R 13 SubTotaal Artikel 50-000483 BESCHUIT ZACHT BROS 24 R 14 SubTotaal Artikel 50-000497 BESCHUIT SMARIUS 24 R 15 SubTotaal Artikel 50-001009 ECHTE BESCHUIT 16X3R 16 SubTotaal Artikel 50-010030 TWENTSCHE BESCHUIT 1X6R 17 SubTotaal Artikel 50-000620 NAT.BESCHUIT NR.1 12X2R 18 SubTotaal Artikel 50-000401 BESCHUIT ZACHT BROS 48 R 19 SubTotaal Artikel 50-009101 BESCHUIT VITAAL 13 ST 20 SubTotaal Artikel 50-004020 BESCH VOLKOREN ZB 8X3 R 21 SubTotaal Artikel 50-003815 KNUSPERB VK GHD 017 24 R 22 SubTotaal Artikel 50-000803 BESCH BOLL WEIZEN 100 G 23 SubTotaal Artikel 50-005110 BESCH MEERGRANEN 4X3 R Average total inventory SKU's Average total inventory (SKU's + MTO articles Average Total Inventory MTO articles. Unit price per box € 11,41 € 5,82 € 5,65 € 19,49 € 6,30 € 3,84 € 4,93 € 3,15 € 3,52 € 5,63 € 6,10 € 11,64 € 5,71 € 5,56 € 11,64 € 2,08 € 6,02 € 11,14 € 3,19 € 6,29 € 5,97 € 5,58 € 4,11. average inventory (pallets) 166 146 111 89 105 80 50 53 45 39 33 41 34 28 22 13 12 12 10 5 7 4 2 1.121 1.225 102. average inventory level (boxes) 3.276 6.282 5.476 1.310 4.033 5.396 3.840 4.026 3.006 1.465 1.254 624 1.266 1.182 419 1.372 473 253 726 178 145 79 57 48.035 53.476 5.349. average inventory level (CU) 157.250 150.778 131.435 104.830 96.797 64.750 46.083 48.309 36.067 35.164 30.087 29.971 30.390 28.379 20.106 8.230 11.353 12.141 8.715 4.280 3.482 1.903 681. average inventory value € 37.380 € 36.564 € 30.942 € 25.539 € 25.409 € 20.720 € 18.932 € 12.681 € 10.580 € 8.249 € 7.647 € 7.268 € 7.230 € 6.575 € 4.876 € 2.853 € 2.848 € 2.818 € 2.317 € 1.122 € 866 € 443 € 233 € 279.986 € 310.643 € 30.657. Table 1. Inventory data for all biscuit rusk SKU's. For article 485 the average inventory level comprises of three average week demand volumes. This seems unnecessary high as variability of week demand is very low for this article as presented in Appendix C. Generally can be said that variability of week demand is low for all articles. So average inventory levels of 2 weeks of demand seem high from a demand perspective especially as the required delivery lead-time is at least two days. The average inventory levels did many times not count up to two average week demand volumes. This reflects mainly experienced problems in production but fluctuations also stem from irregular planning practice for some items. In week 26 the total inventory level was 1400 pallets and inventory levels were conform their targets. For an indication of current inventory costs of holding pallets of biscuit rusk on stock the identified cost factors can be held against the inventory value in the above Table. Appendix D shows that inventory holding costs for biscuit rusk FGI can account for €85.000,- per year.. 24.

(25) 3.4 Conclusion This chapter explained that at Bolletje inventory is controlled by setting arbitrary minimum target inventory levels, usually as 2 weeks of forecasted demand, as to assure the required service level of at least 98,5 % and preferably higher. Actual inventory levels reflect this procedure. Given the low variability of week demand for most articles and a required delivery lead-time of at least 2 days these inventory levels seem a bit high even when production is not completely reliable. It was argued that current IC policy is not really a policy of controlling inventory taking into account sales, planning and production targets, but rather a way of using inventory to reach targets with the greatest amount of flexibility and security. It is clear that the costs of holding inventory are not taken into account. Either way, the current IC policy was identified, thereby answering sub question 1: ‘How is inventory currently controlled at Bolletje?’ Sub question 2 was: ‘What are the costs of holding inventory at Bolletje?’ Cost drivers for the costs of holding inventory were identified from literature and each was discussed from Bolletje’s perspective. Inventory costs relevant for IC at Bolletje include capital costs, handling costs and risk of obsolescence. Handling costs are 2 euro per pallet produced to stock. Capital costs and risk include annually a 10 % and 2 charge respectively over inventory value. Insurance and tax are other inventory costs but it was argued that they shouldn’t be included in IC decision making. Furthermore, due to limited storage space in the master plan external handling and storage costs should be included in inventory decision making. These will be discussed in chapter 5 which concerns the master plan situation. Using the data that was available an indication of inventory costs per year was calculated which shows that inventory holding costs for biscuit rusk alone can count up to approximately €85.000,-. With the above summary sub question two has been answered.. 25.

(26) 4. Literature review: existing concepts and models for inventory control. This chapter will provide a short overview of IC literature introducing well known concepts and models. Then concepts will be selected which are relevant to determine a model for Bolletje’s case.. 4.1 Inventory control through order policies In IC literature many articles and textbooks are available providing a broad perspective on inventory control. This gives an indication of the importance of this subject. Axsäter (2000) argues that the total investment in inventories is enormous and the control of capital tied up in inventory offers a very important potential for improvement. He further argues that scientific methods for inventory control can give a significant competitive advantage. Besides focusing on techniques of forecasting (which will not be discussed since Bolletje works already with a customized software program with a pre-programmed ‘moving average-like’ algorithm) IC literature is mainly focused on ordering methods for both orders towards a supplier of raw materials or a production order for supply of finished goods. The main focus in literature is on batch ordering and the models are divided in two broad groups: •. Deterministic models: which assume deterministic (known with certainty) demand;. •. Stochastic models: assume stochastic (unknown) demand.. And independent on to which group models belong they can distinguish between: •. Single item policies;. •. Multi item policies.. The next two paragraphs will discuss deterministic and stochastic models separately and will both discuss single versus multi item policies.. 4.2 Deterministic models All deterministic models try to seek an optimal policy based on a minimization of a total cost function. The total cost function normally includes an ordering costs term, an inventory holding cost term and for ordering of raw materials a purchasing cost term. Most models try to fix either the order quantity at its optimum or the order interval/cycle. Naturally, when one of the two is fixed the other is fixed as well. Examples of deterministic models relate to either constant demand as the classic Economic Order Quantity Model (EOQ) and the basic Economic Lot Scheduling Problem (ELSP) or to time varying demand as the Wagner-Within algorithm and the Silver Meal Heuristic. ELSP is specifically a multiitem model and the EOQ and related models can easily be adapted to cover multiple items as well. Multi-item models are meant for situations in which it is advantageous to order groups of items 26.

(27) because of price discounts (raw material ordering) or shared setup costs (production orders). For both types of orders shared transport costs can also make multi-item ordering more interesting. The ELSP problem has many variations described in lots of articles. In general can be said that it can be used to determine optimal order cycles to be used in a cyclic production schedules. The basic model is explained among others by Axsäter (2000) and Zipkin (2000). The classic EOQ model and related models as the Economic Production Quantity (EPQ) model or the Economic Order Interval (EOI) model are well described by Tersine (1994). Since these models assume that demand is constant, inventory levels would be determined completely by the order quantity or order interval.. 4.3 Stochastic models For inventory control purposes the mentioned deterministic models are sometimes used to determine the order quantity or interval to be inserted as an input variable in a stochastic model. Two major stochastic inventory control models can be identified: The s,S model and the R,Q model. Both are based on setting a reorder point (s or R) but the s,S model uses a variable order quantity (S) while the R,Q model uses a fixed order quantity Q. Ordering takes place when at the review moment the inventory position has declined below s or R. The inventory position is defined as:

(28) Stock on hand is the same as the inventory level. Normally, IC literature defines outstanding orders as orders that have not yet arrived and defines backorders as orders that have been demanded but not yet delivered. Riezebos (2006) and Riezebos and Gaalman (2006, article in press) recently introduced the concept of order crossovers in IC literature though. They explain that order crossovers occur when orders do not arrive in the same sequence as they were ordered. This can occur when one order has a shorter lead-time than its predecessor. In case of order crossovers the above definitions of inventory position and backorders are not valid. When order crossovers can occur the outstanding orders term should include orders that are ordered in the future (when known in advance) but arrive before the current order does. This can be vital when required safety stock is determined based on forecasted demand in an order-up-to-policy with stochastic demand, known ordering moments and known lead-times. Riezebos and Gaalman (Article in press) argue that this is the case in many standard inventory modules of ERP systems. Reviews of the inventory position can take place continuously or periodic. In Figure 8 on the next page a graphical presentation of the working of both the R,Q and the s,S model is given in case of continuous review. Demand occurs batch wise instantaneously which results in inventory levels below the reorder points. For the s,S model the level S can then still be reached when no demand takes place 27.

(29) during replenishment lead-time (L) because the order that will be placed will reflect the actual inventory position. For the R,Q model, Q remains the ordered quantity independent of the actual inventory position.. R+Q. S Inventory Level. Inventory Level. Q R. s. L. L. L. L. Time. Time. Figure 8. Graphical presentation of R,Q model (left) and s,S model (right). Note that the s,S model with continuous reviews doesn’t fix the order quantity nor the order frequency. Generally the s,S model is known as a continuous model but Axsäter (2000) presents the model also with periodic reviews. In such a case reviews take place periodic but order quantities remain variable. Also for the periodic s,S model the reorder point (small s) needs to be higher than for the continuous review model as the safety stock needs to buffer against review period demand variability. Obviously, if the review period is short enough periodic models are not much different from continuous models. In these stochastic models the reorder point also determines the safety stock which buffers against demand variability, demand during replenishment lead-time and demand during the review period if applicable. The reorder point can be calculated based on a service level constraint or based on minimization of total costs including a backorder cost term or a cost of lost sales term. In any case the underlying demand distribution for an item has to be determined, which is quite complex. Therefore, the demand distribution is usually assumed to be presented by well known and practical demand models as the normal distribution, the compound poisson distribution or the gamma distribution. For a discussion of demand models see Axsäter (2000, chapter 5). Almost every basic model can be extended to reflect a practical or just a more complex situation. For instance when extending a periodic s,S model to include multiple items easily applicable in cyclical planning it basically becomes what Fung, Ma and Lau (2001) call a coordinated T,S model. Not all possibilities will be summarized. Rather is concluded that IC models can be selected to work with: -. A single item versus multiple items. -. Fixed order quantities versus variable order quantities. -. Periodic reviews versus continuous reviews of the inventory position 28.

(30) -. Total cost constraints versus service level constraints. Further models can be adapted to many assumptions of which the most common are: -. Deterministic demand versus stochastic demand with an underlying demand distribution. -. Constant replenishment lead-time versus stochastic replenishment lead-time. 4.4 MTO/MTS decision What generally has not been considered by IC literature is the decision to produce products on a MTO basis or on a MTS basis. D’Allesandro and Baveja (2000) propose to perform demand analysis to aid this decision. For the case study that they discuss (chemical specialty industry) they suggest that high volume - low variability items should be assigned a MTS policy for creating production efficiencies. For low volume high-variability they then suggest a MTO policy as they argue that these items require disproportional amounts of inventory to buffer against the variability. In their case the original situation showed inventories for low volume items equating inventories for high volume items . For Bolletje this is absolutely not the case as can be extracted from Table 1 (p. 24) and Appendix C together. Neither will Bolletje be able to use flexible, or just longer lead-time quoting, as suggested by D’Allesandro and Baveja (2000). Given the goal of inventory reduction it would therefore be unwise for Bolletje to reapply an MTO/MTS policy as suggested by D’Allesandro and Baveja on current MTS biscuit rusk items. For Bolletje the greatest results would be generated when high volume items would be assigned a MTO policy. No literature has been found that reflects on the situation in which the MTO/MTS decision will be reevaluated over the current MTS portfolio to look for opportunities to reduce inventory substantially. The case study performed by D’Allesandro and Baveja introduces is different from Bolletje. Therefore, the selection of new MTO items, and the requirements that will be tested, have to be identified in a practical approach useful for Bolletje’s particular situation. It is obvious that high volume items (also having the highest inventory levels) will be most interesting for MTO production in Bolletje’s case. The decision to be made will be discussed in chapter 6.. 4.5 Conclusion A literature review was presented in this chapter identifying relevant IC policies. Some basic models where explained while options for extending these models to fit more complex or realistic situations were also listed. This provides the first part of the answer to sub question 3: Which concepts and models to perform inventory control identified in literature can be applied to Bolletje’s case? In the next chapter the master plan situation will explain constraints and assumptions to be used in identifying a good IC policy for Bolletje. Then in chapter 6 the actual policy determination can be performed. 29.

(31) 5. The master plan situation described. This chapter will elaborate further on the master plan situation since the model to be selected for Bolletje should work in this new ‘environment’. Furthermore, assumptions will be made about setup and external storage costs as they will have to play a role in determining IC policies.. 5.1 Internal and external storage When focusing on biscuit rusk, two new lines will be located close to the original warehouse and the loading docks. Since the loading docks remain in the same place handling activities will decrease for MTO items in the master plan. Yet, when products are MTS, handling activities related to storing and picking of pallets in the warehouse will not be decreased. Handling costs will therefore not decrease unless more articles will be selected for MTO production. What directly does concern the master plan situation in terms of storage is the space available for internal storage and the directly related need for external storage. The current warehouse space available for storage contains approximately 6000 pallet places (as recently determined with the warehouse manager). This is the net number of pallet places as it accounts for space for transport and movement needed in the warehouse as well as maximum attainable utilization of certain areas. An analysis performed together with the MPS Planner and the Material Manager revealed that approximately 4000 net pallet places will be available in the master plan situation (see Table 12 in Appendix B). It concerns pallet places in the red marked area’s in Figure 2 on page 9. The assumption was made that all net floor space will have shelves as to enable pallets to be piled up. The reduced storage space (2000 pallet places are lost) stems from reduced available floor space as well as reduced possibility for piling up pallets. Generally most floor space available in the master plan enables columns of only 2 pallets while the current storage space has place for 3 pallets to be piled up. On the other hand the assumption was made that all storage areas will use shelves to enable piling up of pallets. This is currently not the case. Bolletje currently uses a storage method somewhere along the continuum running from randomized storage towards fixed storage. Tompkins, White, Bozer, Frazelle, Tanchoco and Trevino (1996) explain that with randomized storage individual SKU’s can be stored in any available storage location. Opposed to this concept is dedicated storage or fixed slot which means that SKU’s have their own floor space available which must accommodate their maximum inventory level. Different product families normally have a specific area where their pallets are stored but the pallet places being used are not strictly limited. For biscuit rusk this means that all biscuit rusk items are stored closely together. Like for all products of Bolletje FEFO (First Expired First Out) picking is used. Storage area’s for biscuit rusk are divided in rows (with differing capacities) and rows are used by one specific article only. While any row can contain any article (randomized storage), a row 30.

(32) becomes dedicated (fixed storage) as soon as one or more pallets of a specific article are stored in the row. Different best-before-dates cannot be stored in the same rows resulting in more strict fixation of storage space. It has to be noted that Bolletje changes its best-before-date every four weeks. Since currently a form of randomized storage is used it can be assumed that any pallet of inventory structurally reduced results in a pallet place that can be used for internal storage of seasonal products. And that would result in less external storage costs. It is assumed that the same storage method as currently applied will be used in the master plan. Currently and in the master plan, seasonal pallets are stored externally when internal capacity becomes insufficient. The capacity for internal storage of seasonal pallets in both the current and the master plan situation can then be presented, as in Table 2 below, based on average inventory levels of all finished goods families.. Pallet places needed in current and master plan situation based on average inventory level per product family (pallets) Biscuit rusk 1300 Toast 50 Knäckebröd 1000 Koek 450 Sticks 300 Roggebrood 100 Brood 100 Bi/Ba 350 Kruidnoten/Seasonal 3000 Wafels 25 Pita 200. pallets pallets pallets pallets pallets pallets pallets pallets pallets pallets pallets. Total average inventory Total av. Inv. without seasonal Currently availabe Master plan available Available for seasonal currently Available for seasonal master plan. 6875 3875 6000 4000 2125 125. pallets pallets pallet places pallet places pallet places pallet places. Max. seasonal inventory 2008. 4700 pallets. External storage currently average max. 875 seasonal pallets 2575 seasonal pallets. External storage master plan average max. 2875 seasonal pallets 4575 seasonal pallets. Table 2. External storage evaluated based on randomized storage.. Table 2 presents the average inventory levels for all product types in the first rows adding to a total of 6875 pallets. It is assumed that these inventory levels present both the current and the master plan situation. It is shown that based on average inventory levels in the current situation 875 seasonal pallets will have to be stored externally (3000 pallets average inventory – 2125 pallet places currently available for external storage) with a maximum of 2575 pallets.. 31.

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