2. RESEARCH CONTEXT
2.5 Performance measures
The performance of the factories is measured on either a monthly or weekly basis by a number of key performance measures (KPIs). A KPI is a performance measure that evaluates the success of an organisation. Together with SCCE, the factories have defined four KPI-groups that consist of a number of KPIs. These groups are: employees, process, customers, and financial. Within the customers-group, there are two critical KPIs: on time and complete performance of the factories and on time and complete performance of the suppliers:
๐๐ ๐ก๐๐๐ ๐๐๐ ๐๐๐๐๐๐๐ก๐ =# ๐๐๐๐๐๐๐๐๐๐ ๐๐๐๐๐ฃ๐๐๐๐ ๐๐ ๐ก๐๐๐ ๐๐๐ ๐๐๐๐๐๐๐ก๐
# ๐๐๐๐๐๐๐๐๐๐ โ 100%
SSCE expects the factories to have a 95% on time and complete performance and the factories expect their second tier suppliers to have a 98% on time and complete performance.
10 3. RESEARCH SCOPE
In Chapter 2, the research context is discussed. The chapter finalises with performance measures of factories. This chapter analyses the actual performance of this performance measure. Moreover, performance of second tier suppliers is analysed and a specific type of equipment that is used as a business case for the research project is discussed.
3.1 Factory performance
The on time and complete performance target for the three factories is 95%, and is measured by SCCE.
Graph 2 illustrates the performance of VIM in 2016, and Graph 3 the performance of VIS in 2016. VIS did not have production before week 10, therefore there is no data concerning weeks 2-10. The records of VIA are not tracked yet, which is why the performance of this factory cannot be measured. The average percentage for on time and complete orders of VIM is 83%, with a minimum of 68% and a maximum of 94% over on average 64 orders per week. VIS finishes on average 65% of its orders on time and complete.
In week 35, VIS reached a minimum of 33% and in week 32 a maximum of 100%. It can be concluded that the average performance of both factories is a lot lower than the threshold of 95%. VIM is, based on data from this period, compared to the threshold underperforming with 12% and VIS with 30%.
Graph 2, Weekly performance VIM
Graph 3, Weekly performance VIS
3.2 Cause-and-effect diagram
If a factory does not deliver the material on time and complete in the requested week, the order is delayed and a reason for the delay is captured in the ERP-system. Every week, SCCE checks these reasons
0%
Delayed or incomplete On time and complete On time and complete %
0%
Delayed or incomplete On time and complete On time and complete %
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and there can be only one reason for one delay. The reasons are categorised into 5 main groups and illustrated in a cause-and-effect diagram displayed in Figure 6. A cause-and-effect diagram helps to trace the roots of a problem and organize them (Ishikawa, 1990).
Per branch, the proportion of the cause compared to other causes is computed and illustrated in a pie-diagram in Appendix F. 35% of the delays are due to overdue purchase parts, 30% due to excessive workload, and 13% due to human mistakes. Hence, the overdue purchase parts lead to most delays and therefore this research focusses on material availability to increase factory performance.
Radke and Tseng (2012) compared ETO and MTO organisations in terms of product structure and concluded that in ETO companies, nearly half of the purchase items are common parts, used in multiple projects. For those parts, the ordering of materials can be standardised and the CODP can be placed at the manufacturing process instead of at the purchase process. Standardisation of the ordering process can lead to higher material availability. Vanderlande has one material handling system that is considered to be standardized in terms of purchase parts and that is produced by all Vanderlande factories. This material handling system is the Posisorter.
3.3 Posisorter
Posisorter is abbreviated to SPO (SorterPosi), and it is a product suitable for the parcel and postal market, of which many projects are being sold. Vanderlande persists on producing a part of the equipment in the own factories, and in contrast to other equipment, Vanderlande finds it easier to predict future sales concerning these projects. Moreover, this product has not experienced many developments in the past years and the Research and Development department does not expect many changes in the near future.
The SPO is a line conveyor sorter that delivers products by means of sliding shoes (Figure 7). A SPO is split up into six components and the production of the components is executed by the following parties:
- Component (A) is produced by subcontractors;
- Component (B) is produced by VIM;
Figure 6, Ishikawa diagram of factory performance
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- Component (C) is produced by VIM, VIA and a subcontractor;
- Component (D) is produced by subcontractors;
- Component (E) is produced by subcontractors;
- Component (F) is produced by VIM, VIS, and VIA.
The components that are fully outsourced are left out of the scope of the research. Thus, the research project considers the production of component (B), (C), and (F). However, one single subcontractor is included as this subcontractor produces sub-components of component (F), a component that is also produced by the factories. The performance of the on time and complete delivery of the subcontractor is not known and therefore not added to the report. There are different ways to compute the amount of sub-components required for a system. Component (B) is measured in number of projects, as only one component is required for one project. Component (C) is measured in number of exits, and component (F) is measured in meters.
Figure 7, Layout of the Posisorter
SPO Future demand
SCCE collects information of sold SPO projects to determine future workload. There are two types of information: SPO forecast information, which concerns sold projects with an unfinished detailed design, and SPO ordered information, which concerns sold projects with a finished detailed design. Graph 4 illustrates the future demand. Information about the meters can be used to approximate workload and demand for SPO projects.
Graph 4, SPO Future demand in meters
There is a division between SPO meters that are assigned to VIM and to VIS, and this decision is based on the material of component (F). If component (F) is made out of steel, it is allocated to VIS, and if it is made out of plastic, it is allocated to VIM. Graph 3 also displays not assigned forecasted meters that still
0 200 400 600
43 44 45 46 47 48 49 50 51 52 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17
SPO meters
Week
Posisorter Future demand
VIM Forecasted VIM Ordered VIS Forecasted
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have to be assigned to a factory. VIA is not mentioned by the forecast, as the factory is not yet producing SPO equipment. It will start with its production in spring 2017. The horizontal line in the graph displays the 400 meter barrier representing the total maximum capacity of the factories, as VIM and VIS can each produce approximately 200 meter per week. In the future, VIA will be able to produce 100 meter SPO.
SPO purchase items
The planned lead-time for a second tier supplier to deliver material to a factory is always four weeks.
The list with purchase items required for the production of component (B), (C), and (F) consists of 76 items. 28 of these items have a standard lead-time longer than four weeks, 37 items have a standard lead-time of four weeks and eleven items have a standard lead-time that is shorter than four weeks.
37% of the orders delivered within Europe thus has a standard time longer than the planned lead-time. Moreover, the actual lead-time of the supplier can deviate from the standard lead-lead-time.
3.4 Second tier supplier performance
VIM and VIS keep track of the weekly performance of the second tier suppliers by measuring the Delivery to request performance of the suppliers. The definition is defined in Table 1.
Table 1, Performance measures second tier suppliers
KPI Definition
Delivery to request The KPI shows if the supplier is able to deliver according to the request date, set four weeks after the order date. The performance per order line is set as:
๐ท๐๐๐๐ฃ๐๐๐ฆ ๐ก๐ ๐๐๐๐ข๐๐ ๐ก ๐๐๐ ๐ค๐๐๐ =
# ๐๐๐๐๐ ๐๐๐๐๐ ๐ค๐๐กโ ๐๐๐๐๐๐ฃ๐๐ ๐๐๐ก๐ โค ๐๐๐๐ข๐๐ ๐ก ๐๐๐ก๐, ๐๐ ๐๐๐ ๐ค๐๐๐
# ๐๐๐๐๐ ๐๐๐๐๐ ๐๐๐ ๐ค๐๐๐
Graph 5 shows the Delivery to request performance of the second tier suppliers of VIM and Graph 6 the Delivery to request of the suppliers of VIS. Both factories request a 98% delivery performance. The suppliers of VIM have an average performance of 80%, with a minimum at 75% and a maximum of 87%.
The Delivery to request of the suppliers of VIS is on average 83.3%, with a minimum of 72.1% and a maximum of 93.5%. It can be concluded that the second tier suppliers of VIS perform better than those of VIM, but that the performance of suppliers to both factories is more than 10% lower than strived for.
Graph 5, Delivery to request, second tier suppliers VIM
0%
Delivery to request second tier suppliers VIM
Orderlines Delivery to request
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Graph 6, Delivery to request, second tier suppliers VIS
It is not possible to filter the factory performance on specific equipment, as the data used to measure performance does not contain information about the type of equipment. Nevertheless, the performance of second tier suppliers can be filtered on SPO data. Appendix G, Graph 8 illustrates the SPO performance of the SPO suppliers in VIM. On average, the SPO suppliers of VIM have a performance increase of 5%
compared to the total set (Table 2). The delivery performance of the SPO suppliers of VIS is based on values from the trial-period in which only a small amount of item numbers were ordered. The average performance of 25 order lines placed in eight weeks is 96% (Appendix G, Graph 9). Due to a limited amount of order lines, a similar table with the results of the comparison is excluded from the research.
Table 2, Comparison of suppliers VIM Factory Veghel
Delivery to request Delivery to request SPO Difference
Average 80% 85% 5%
Minimum 75% 70% -5%
Maximum 88% 100% 12%
The SPO supplier performance is not completely reliable, as for some SPO materials the operational buyers of VIM and VIS place orders beforehand. This results in not proactively controlled stock, meaning that no inventory model is used to determine inventory parameters and that parameters are not proactively updated. The inventory levels are not documented, but it does suggest that the measured performance is higher than the actual performance.
3.5 Conclusion
This research project concentrates on increasing on time and complete performance of factories, as the analysis of section 3.1 showed that they are underperforming in delivering material on time and complete. In section 3.2, it is concluded that factory performance is mostly affected by overdue PIs. The research focusses on SPO data produced by three Vanderlande factories and a single subcontractor. The analysis of the second tier suppliers, executed in section 3.4, revealed that there is a gap between the target level aimed by factories and the actual Delivery to request performance of suppliers. Filtering second tier suppliers on only those who supply SPO material gave similar results. Vanderlande factories and second tier suppliers are using local stock points to increase performance, but this stock is not proactively controlled. Proactive inventory control can increase the material availability and thus performance. Chapter 4 elaborates on research questions defined to create proactive inventory control.
0%
Delivery to request second tier suppliers VIS
Orderlines Delivery to request
15 4. RESEARCH DESIGN
In Chapter 3 it is concluded that factories are underperforming in delivering material on time and complete. A cause of underperformance are PIs delivered later than requested. Analysis of second tier suppliers showed that they are underperforming in delivering PIs at the request date. Local stock points are supposed to increase performance, however target levels are not met. Chapter 4 shows the problem statement, research question, scope and project approach set in order to increase factory performance.
4.1 Problem statement
The research project analyses a two-echelon supply chain involving second tier suppliers, factories and a subcontractor. Vanderlande factories and subcontractors have to receive PIs within four weeks, due to order placement six weeks before order finish date, and two weeks required for production. VIM and VIS are creating stock as a precaution against material unavailability. Decisions for the stock levels are made locally and are not proactively controlled. Furthermore, second tier SPO suppliers are keeping stock to deal with demand uncertainties. Still, actual on time and complete performance is lower than the target level. Based on this information, the main problem for this research project is defined as:
Vanderlande factories and their suppliers are underperforming in delivering material on time and complete for Posisorter projects, whilst keeping local inventory levels that are not proactively controlled.
4.2 Research questions
To reach the preferred service level, second tier suppliers, factories, and subcontractor have to improve control of their inventory levels. Furthermore, considering the system as a whole while using central decision making might increase performance even more.
4.2.1 Main research question
The following research question is determined:
What is the effect of proactive inventory control for the Posisorter equipment on performance of the factories and suppliers?
4.2.2 Sub-questions
This question is be divided into six sub-questions, answered during the research project:
1. What are measurable performance indicators for the factories and suppliers?
2. What is the performance of the current approach for uncontrolled stock points in the factories and at Vanderlande suppliers?
3. How do the factories and suppliers perform if they use local stock points and make local decisions?
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4. How do the factories and suppliers perform if they use a central stock point at the supplier, no stock points at factories and make central decisions?
5. How do the factories and suppliers perform if they use central and local stock points and make central decisions?
6. What is the difference in performance between proactively and non-proactively controlled stock points?
Sub-question 1 and 2 are answered in Chapter 3, sub-question 3 to 5 are discussed in Chapter 5, and sub-question 7 is answered in Chapter 8.
4.3 Project scope
Shrivastava (1987) stated that a more detailed project increases feasibility, but simultaneously decreases scientific relevance. Consequently, this research project focusses on a two-echelon supply chain incorporation four factories (VIM, VIS, VIA, and a subcontractor) and second tier suppliers.
Furthermore, solely data concerning the SPO projects is used for the analysis. The goal is to design an inventory model for all PIs required in SPO projects. This scope results in a project detailed enough to ensure a certain level of feasibility, and scientifically relevant as literature concerning local and central inventory control policies can be used.
4.4 Project approach
The regulative cycle of Van Strien (1986) is used during the master thesis project. According to Van Aken et al. (1997), the regulative cycle consists of five process steps: problem definition, analysis and diagnosis, plan of action, intervention, evaluation. Figure 8 illustrates the steps and the activities executed for the research project. The master thesis project only concerns the first three steps, though the conclusion and recommendations of the master thesis report can discuss useful insights for the intervention step.
Figure 8, Regulative cycle by Van Strien (1975)
During the research, it has been important to find the right balance between rigour and relevance. In explanatory research the aim is to generate objective generic knowledge based on theories, whereas Field Problem Solving (FPS) has the aim to generate specific knowledge, and solve a specific business performance problem. The goal of the thesis is to make a contribution to both: improve the performance of the factories at Vanderlande and add something to existing literature. The model of Van Strien (1986) provided guidelines during the project, to ensure a both rigour and relevant research is conducted.
17 5. CONCEPTUAL INVENTORY CONTROL MODEL
In Chapter 4, it is concluded that proactive inventory control can increase factory performance. This chapter first discusses KPIs, in order to answer sub-question 1, next it elaborates on three conceptual inventory control models, in order to answer sub-question 3 to 5, and the chapter finalises with an analysis of the demand used as input for the models.
5.1 KPIs
Radke and Tseng (2012) emphasize that an ETO company should make a trade-off between low inventory budgets, high service level, and short delivery lead-times when determining the inventory levels. This trade-off can be translated into three KPIs, applicable in the supply chain of Vanderlande (Table 3). The high service level is similar to both the on time and complete performance of the second tier suppliers and the material availability at factories, resulting in the first two KPIs. The factories do not have an inventory budget, but Vanderlande strives to minimize its total costs, being the third KPI. Lead-time between the second tier supplier and the factory is assumed deterministic and is not translated into a KPI. The first KPI is indirect, as it directly affects the suppliers but indirectly affects Vanderlande, whereas the other two KPIs directly affect Vanderlande.
Table 3, Key Performance Indicators set for Inventory Control
KPI Definition
On time and complete performance
The percentage of order lines delivered on time and complete by a second tier supplier.
Material availability The percentage of order lines fulfilled from stock for the factory.
Costs The total costs of the inventory of the two-echelon supply chain.
An organisation optimises its inventory by finding an optimal balance between the inventory level, resulting in performance, and inventory costs. If material for orders cannot be picked from stock, this results in back-orders or penalty costs. Unfortunately, the penalty costs cannot be computed for Vanderlande, as those vary per project. Nevertheless, customer satisfaction is of great importance and the cost of losing customer goodwill can be immense. Instead of computing penalty costs, a service level is introduced, to ensure a high performance level (Bijvank, 2013). For Vanderlande this means that 98%
of the order lines should be delivered on time and complete. The objective function of the inventory model is therefore to minimize the costs subject to the service level constraint.
5.2 Conceptual model
The structure of an inventory model that is applicable, is a distribution system that consists of a single supplier and multiple buyers. Within Vanderlande, the second tier supplier is the supplier and all factories and the subcontractor are the buyers. Per sub-question the conceptual model is discussed.
5.2.1 Local inventory and local control
The first situation is a model considered by sub-question 3. In a locally controlled situation, the distribution system of Vanderlande would look like Figure 9. Demand arrives at the buyers and proceeds
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to the supplier. The supplier then supplies the buyers. Every location has its own inventory model, which is controlled in a decentralised perspective.
Figure 9, Situation 1: Local decision making and local stock points
5.2.2 Local inventory and central control
The second distribution model is illustrated in Figure 10, and refers to sub-question 4. A decentral distribution model with five decision makers that locally control the inventory, can be organized differently by shifting from five decision makers into one decision maker, changing it into a central distribution model. In a centralised perspective, the decision maker has information of all locations and the goal is to optimise the system as a whole, instead of optimising the local stock points.
Figure 10, Situation 2: Central decision making and local stock points
5.2.3 Central inventory and central control
A special type of a central distribution system is one with zero inventory levels at the buyers. This is the third situation, reflected by sub-question 5 and displayed in Figure 11. In this situation, solely suppliers keep stock.
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Figure 11, Situation 3: Central decision making and central stock
Figure 11, Situation 3: Central decision making and central stock