AKZO Nobel

Appendix A Organisation and study scope

AKZO Nobel

Appendix B Introduction to products and markets

In this Appendix a short introduction will be given to the markets the MPC plant serves. Firstly, a brief introduction is given to AKZO Nobel Catalyst’s main customer base, the oil industry. The second part of the Appendix focuses on the seven product groups of the Multi Purpose Catalyst Plant and its market expectations.

The oil and catalyst industry

There is a variety of products that stems from crude oil, such as plastics, heating oil, jet fuel, tires, gasoline, etc... In order to manufacture these products, crude oil needs to be processed first to obtain the hydrocarbons from the crude oil. Hydrocarbons vary in molecular weight and boiling point and can be separated by crude oil distillation. For example, petroleum gas, used for heating, cooking and making plastics, is the smallest of alkanes (1 to 4 carbon atoms) and has a boiling range of less than 40 degrees Celsius. Heavy gas, used as the starting material for other products, contains between 30 to 70 carbon atoms and has a boiling range from 370 to up to 600 degrees Celsius. To increase the yield of gasoline, oil companies chemically process fractions from the distillation column. One method of changing fractions is by cracking. Cracking is the breaking down of large hydrocarbons such as heavy gas into smaller molecules. There are several ways to crack large hydrocarbons, but for the thesis only catalytic cracking is of interest.

The biggest markets for catalytic cracking are Fluid Cracking Catalysts (FCC) and Hydro Processing Catalysts (HPC). FCC cracks heavy gas into diesel oils and gasoline at a temperature of 538 degrees Celsius. HPC cracks heavy oils into gasoline and kerosene, but at a lower temperature and higher pressure with the help of hydrogen gas.

Figure I Oil cracking

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Expected global oil and catalyst market development

During the period 2000 to 2003, Global catalysts sales increased by 6 per cent, to US$12.1 billion, but growth is expected to slow down to 3.7% between 2003 and 2008. The strongest sales projected will be in Asia, particularly China, as well as Latin America. Europe rather will experience a strong decline in sales growth, from 11,1 per cent during 2000 to 2003 to 3,7 per cent from 2003 to 2008. Sales growth in the US will level over the period; from 2,9 per cent to 3,0 per cent (Chemical Week, 2004). Worldwide petroleum refining catalyst sales are projected to grow by 2,5 percent in 2003-2008, to just over USD 1 billion. Global sales of chemical processing catalysts will increase by 3 per cent, to USD 4.8 billion during the same period.

Markets of the Multi Purpose Plant

This part of the section focuses only on the important products of the Multi Purpose Catalyts plant, as identified in chapter 1. The plant serves four markets: the Fluid Cracking Catalysts, Hydro Processing Catalysts, Oxychlorination and Specialty market.

Fluid Cracking Catalysts market

Additives: For three years, AKZO Nobel Catalysts has been active in the Additives market.

There are five types of Additives produced at the MPC plant: KOC 15, KDSOX

Resolve 750, Resolve 850 and Resolve 950. Additionally, more Additives are produced at the AKZO Nobel Catalysts’ plant in Deer Park (Pasadena) in North America, amongst others KDNOX, Resolve 700 and Resolve 800.

Additives are catalysts that enhance the performance or reduce sulphur in the production of FCC gasoline. Due to stricter environmental regulations, refiners more and more turn to Additives to meet new clean fuel legislation enforced by governments around the world. The Business Development Group does not own this product group. The products are manufactured and sold at an internal transfer price. Currently, Additives are benefiting from market growth. A substitute for this product is to modify the plant. For this reason, the customers are in a way price sensitive. In November a project was slated in the MPC and FCC plants, to smoothen production. Marketing of Additives is done by the Additives organisation in the States.

QTY (Mt) 2000 2001 2002 2003

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Additives X X X X X X X

Hydro Processing Catalysts market

KF 542: KF 542 catalysts are produced for the HPC market, sold at an Internal Transfer Price too and serve as a protection layer on top of the regular HPC catalysts. The catalyst is also referred to as a Guard bed catalyst. This is an important feature considering the fact that HPC catalysts on average remain one-and-a-half years in a reactor. A second attribute of KF-542 is its ability to smoothen the flow of crude oil through the reactor. Currently the product’s demand exceeds production due to unavailability of raw materials from the HPC plant. The CPU manager is trying to import material from the United States.

QTY (Mt) 2000 2001 2002 2003

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KF 542 X X X X X X X

Oxychlorination market

FPC-2 LD: This product was developed in cooperation with Formosa Plastics Corporation (FPC) and is used as a catalyst in the production of polyvinylchloride (PVC). The production of FPC-2 LD takes place under license from Formosa Plastics Corporation. The decline of this product is partly due to the strong correlation of PVC consumption with the economic recession. In addition, customers are becoming ever more efficient in their production processes.

QTY (Mt) 2000 2001 2002 2003

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FPC-2 LD X X X X X X X

EasyOX-1: Akzo Nobel has been producing oxychlorination catalysts for over 25 years, both under license and for open markets. In 1998, AKZO Nobel Catalysts introduced its own Oxychlorination catalyst. However, sales of this product are currently falling short. This can be explained by price sensitivity of the product as one large customer currently benefits from a more favourable Dollar/Euro rate. Rivalry in this market is relatively high as competitors offer similar catalyst qualities at virtually equal price.

QTY (Mt) 2000 2001 2002 2003

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EasyOx-1 X X X X X X X

Chemical Industries

KDC-6-5P: The KDC-6 catalyst is used in the production of Methylamines. Methylamine serves as an intermediate for the chemical industry and covers a variety of applications in detergents, agrochemicals, feed additives, pharmaceuticals, solvents, pulp & paper processing, flocculants, PU catalysts and explosives.

QTY (Mt) 2000 2001 2002 2003

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KDC 6-5P X X X X X X X

FEK-2: FEK-2 was developed in co-operation with ESSO and is produced on contract basis. This contract will end in 2006. FEK-2 is used in the production of white oil and finds applications in the food processing, cosmetics, hair care, plastics, pharmaceuticals, textiles and other industries.

QTY (Mt) 2000 2001 2002 2003

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FEK-2 X X X X X X X

Acrylonitrile (ACN): C49 MC and C491 MC are toll-manufactured for British Petroleum (BP) on contract basis, which is currently silently extended on an annual basis. ACN finds its application in the production of Nylon. BP uses the MPC plant as their backup plant and BP is the sole supplier of this product in the world.

QTY (mt) 2000 2001 2002 2003

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ACN X X X X X X X

Appendix C SCOR model

SCOR model

At SBU EUMEA, the company’s internal supply chain is analysed by means of the Supply Chain Operations Reference (SCOR) model. The SCOR model is a standardised business process reference model developed by the Supply Chain Council (SCC). The SCOR model was originally developed as a standard reference model that could be used by organisations in any industry segment for sharing information with supply chain partners. However, it developed into a tool for describing, analysing, and improving the supply chain.

Figure II SCOR model framework

The original SCOR model was organised around four management processes (building blocks):

plan, source, make and deliver. Subsequently, a fifth building block could be added called return.

SCOR Process Definitions

Plan Processes that balance aggregate demand and supply to develop a course of action which best meets sourcing, production and delivery requirements;

Source Processes that produce goods and services to meet planned or actual demand;

Make Processes that transform product to a finished state to meet planned or actual demand;

Deliver Processes that provide finished goods and services to meet planned or actual demand, typically including order management, transportation management and distribution management;

Return Processes associated with returning or receiving returned products for any reason; these processes extend into post-delivery customer support.

Table I SCOR’s five core management processes

The SCOR model consists of 150 predefined performance measures divided over three levels.

Level-one metrics can be used as a benchmark or set as business objectives by top- management. Level-one metrics are decomposed into level-two metrics, and level-two metrics can be decomposed into level-three metrics. At level four, the supply-chain levels are system specific and organisations implement specific Supply Chain Management practices at this level.

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By decomposing the top-level metrics into the lower-level metrics, the interdependency between the metrics becomes clear and (strategic) trade-offs have to be made regarding the formulation of the strategy and filling in of the processes.

Figure III The hierarchy of the SCOR model

A survey from Huan et al. (2004) indicates that the SCOR model is a promising model when it comes to strategic supply chain decision making. In contrast to the SCOR model traditional process decomposition models reason bottom-up. In traditional process decomposition models, processes are looked at with a decreasing aggregation level in order to understand what is happening in a particular process. The latter approach is better known as the systems perspective with regard to organisations. The systems theory aims at identifying relations between elements within the considered system. This allows an organisation to undertake specific actions in relation to its functioning as a system and adapt according to its relation with the environment. A useful framework in logistics from a systems theory approach is the logistical concept originally developed by Verstegen (1989). This concept is explained in chapter six and used in this thesis to audit the Multi Purpose Catalysts organisation for possible problem areas in Production Planning & Control. The assumption behind the framework and also systems theory is that every organisation is unique and no governing standards exist that define a business model as differentiation is explicit in competition. This assumption is in contrast to the SCOR model which transforms the organisation (the system) into predefined “Supply Chain” processes. Hence the name process reference model. Mesher (1997) questions SCOR’s ability to make accurate strategic supply chain decisions by pointing out that there has been no published evidence of the SCOR approach to generate good measurement for strategy.

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Appendix D Return on Investment

The Return on Investment (ROI) model, originally developed by du Pont, is an often used tool to express the organisation’s profitability in percentage terms and is a measure of the amount of money a company has invested to generate a certain income. This percentage can be compared to interest rates and can serve as a benchmark tool for investors. As long as the ROI is above the interest rate, it is worthwhile to invest in the organisation. The model expresses the organisation’s Return on Investment in two ratios which should be seen in conjunction with one another:

efficiency and productivity. In this analysis ROI is expressed as a resultant of profit margin times turnover. The model is shown hereunder.

Figure IV ROI model (Atkinson et al., 2001)

Logistics can contribute to a reduction of cost in many different areas in the model. Both turnover

and profit margin are influential logistical elements in the different chains within the organisation

and between organisations. Logistics has the task of tuning these chains by controlling the

operational processes. The biggest leverage of logistics can be found in working capital

reduction, the variable cost of the investments within the organisation. Furthermore, with a sound

logistical concept in place, manufacturing cost can also be reduced. Planning more efficiently,

levelling production, could mean fewer employees are needed in manufacturing while producing

the same output.

Appendix E Ishikawa diagrams

Physical structure

Demarcation lines are vertical lines in a physical structure of a goods flow, indicating that the continuity of the flow is interrupted and the regime responsible for operations has changed (Hoekstra & Romme, 1992). As a result, this may lead to errors and as the demarcation lines grow in number, the risk of cumulative errors will equally grow. The plant can be identified as a shared resource. A shared resource is a machine or department which capacity has to be shared.

Each different sub Business Unit has its own goals and objectives. These different interests may lead to finding sub-optimal solutions. An aspect might look optimal to one sub Business Unit, but may have a negative effect on the objectives of another sub Business Unit.

Production Planning & Control

In their book “Integral Logistic Structures” Hoekstra & Romme (1992) indicate that the various

activities in an organisation should be integrated as much as possible. A control structure should

be developed in which the different interests of stakeholders/departments can easily be

harmonised and trade-offs in production easily be made. Without customer service levels, a

department has little opportunity to communicate its preferences on cost versus service level.

Information system

Adequate and relevant information is needed for a proper control over the production process which at the same time should be relatively easy to be exchanged with relevant parties. Without relevant and reliable information, accurate decision making on for instance stock or logistical improvements is not possible. Island automation is a form of automation in which there are no links or hardly any links between the different information platforms. Additional data have to be gathered to create information.

Organisation

Logistics is meant to streamline the flow of goods within an organisation and has to connect

departments with each their own goals and objectives. Effective and efficient logistics can only be

in place when multiple departments work together (Van Goor et al., 1996). General negative

consequences of departmentalisation according to function and division of influence on the

organisation are elucidated hereunder.

Appendix F Decoupling stock considerations

Introduction and definition

In the thesis the concept of the Decoupling Point is used to distinguish customer orders from forecast-driven orders. The definition of a DP used in this paper has been derived from Hoekstra (1992): the decoupling point is the point that indicates how deeply the customer order penetrates into the goods flow as shown in figure V. Customer driven production originates from the decoupling point, irrespective whether multiple customer orders have been clustered.

Figure V The Decoupling Point (Hoekstra & Romme 1992)

Positioning of the Decoupling Point

According to Hoekstra and Romme (1992:122) the positioning of the decoupling point is

dependent on two questions: How far upstream can the decoupling point be pushed without

losing customers because of too low a performance on delivery? How far downstream can we

push the decoupling point without running into an unacceptable high level of stock costs?

Relevant factors to consider in answering how far upstream the decoupling point can be positioned are:

• The lead time should be shorter than the required delivery time.

• Variations in lead time or in production output make it more difficult to deliver completely and at the agreed time.

• In the case of batch production with significant changeover times and/or initial costs per batch, it is advisable to keep the DP downstream of such a process.

• It is preferable to keep the DP downstream with respect to a complex or high-risk production process, or a very specific, irreplaceable capacity resource.

• It is preferable to keep the DP downstream with regard to a point in the goods flow where materials, components or other contributions are introduced by unreliable suppliers or suppliers who are difficult to replace.

The following are considerations in determining how far upstream the decoupling point can be positioned:

• The closer the stocks lie to the market, the more expensive they are.

• It is difficult to distill a reliable forecast from irregular market demand, which must be offset by high safety stocks.

• Many different product types or versions increase the risk of long waiting times in sources, possibly even leading to some type numbers becoming unsaleable.

• If the potential market comprises of only a small number of customers, there is a relatively high risk of obsolescence (unless our customers have a certain contractual commitment to buy).

• It is preferable to keep the DP upstream with regard to activities specifically intended for a particular market segment or for one individual customer.

• It is preferable to keep the DP upstream with respect to any activity with a relatively high

value added compared with the lead time.

Appendix G Control concepts

Certain decisions play their part around the production process, from the production decision till shop-floor and the direct control of it. Starting point is the customer order which has to be accepted by the organisation in a responsible manner and subsequently released for production.

There are several ways of controlling the coordination of the flow of goods through an organisation. In the research this will be limited to describing Materials Requirement Planning (MRP-I), Manufacturing Resource Planning (MRP-II), Just-in-time (JIT) and Theory of Constraints (TOC). The four control concepts each fall in one of the two basic control variants:

• Production control based on feed forward information. The changes are continuously measured in advance and compared to the norm. Interventions take place prior to the actual manufacturing process. The products are pushed through the system as it were and hence the name push-system for this type of control;

• Production control based on feedback information. Changes in demand pattern are directly measured at the output side and a comparison takes place with respect to the norm and interventions subsequently take place on the input side of the process. This principle is used when customers are able to buy products directly from the organisation.

This system is referred to as a pull-system as customers pull products from the production process. This method only works well in a chain where quick response is possible. That is to say, lead times in the organisation are short.

In the first paragraph the push method will be elaborated on. In this approach the coordination of the flow of materials is governed by MRP-I. MRP-II might be of use when resource capacities are to be utilized to their full potential. The second paragraph focuses on the pull method in which Just-In-Time and control on the basis of bottlenecks will be highlighted.

Material requirements planning (MRP-I)

Control of the MPR-I system consists of a set of calculation rules with which future demand of material can be calculated. As the system makes use of future demand (i.e. forecasting) it is coupled with a feed forward system. The system is based on two basic principles:

• Phasing of time: The time horizon is split in equal periods which are named buckets. The buckets are needed to bring information over the period together and can vary as much as days to several weeks, depending on the accuracy the organizations chooses to plan.

• Dependable demand: The demand of intermediates and raw material is deducted from

the product structure of the final product. Dependant demand is calculated demand and

does not need forecasting. The demand of final products is referred to as independent demand.

The demand of final products is stated in the Master Production Schedule (MPS) and planning of logistics is derived from forecasts and customer orders in the MPS.

Manufacturing resource planning (MRP-II)

Here above the working of MRP-I was explained. Manufacturing resource planning (MRP-II) is a logical successor of MRP-I. MRP-I does not feedback whether production is at all possible. In addition to MRP-I, MRP-II makes use of a capacity requirement plan (Capacity Requirement Planning) per bucket. With this mode the work (over) load per equipment per bucket can be determined. If large deviations appear, it may be decided to reschedule the MPS. In case of smaller deviations, the planner is often able to reschedule orders on the premise the material situation allows this. If sufficient safety stock is kept, orders can also be back-scheduled. In MPR- II a couple of feedback loops have been integrated in the planning to overcome this. Management formulates objectives and on the basis of these product- and market plans a production plan will be formulated. The production plan states total sales that have to be produced. The plan often states monthly production runs per product family. Various units of measure can be used, such as tonnes, standard hours, number of operators, etc… The Production Plan forms the authorisation from management to the MPS-planner to translate this plan into the Master Production Schedule.

Information directly derived from the Production Plan is thereupon roughly compared with the available resources, i.e. total production hours needed compared to the available operators (Rough-Cut Capacity Planning). Important pieces of equipment can also be included. In the MPS it is further checked whether or not it is possible to technically manufacture the final products.

Customer orders and forecasts can be weighed against one another, in order to give a more balanced plan for production.

It is further possible to add other systems to MRP-II, such as Distribution Requirements Planning

(DRP-I) and financial systems, such as Money Resource Planning (MRP-III), see figure VI.

Figure VI MRP-II (Visser & Van Goor, 1994)

Just in time (JIT) and kanban

Just-in-Time (JIT) is a philosophy in which the flow of goods is Just-in-Time manufactured and

the right quantity delivered to realise logistical objectives. The Just-in-Time philosophy focuses

primarily on the transformation process in search for continuous improvement and reducing

control complexity, shortening lead times and reducing inventory. JIT sees inventory as the root

of all evil, because inventory is a result of production and delivery of wrong products, in wrong

quantities, on the wrong location and at the wrong point in time. JIT aims at purposeful exposing

the production organisation to uncertainties in the production process, because problems become

apparent and this provides the possibility to eliminate the irregularities in order to enhance the

logistical performance, a continuous improvement. The Westernised reason for keeping stock

relates to guarding itself against uncertainties and uses MRP–II to overcome irregularities in

production, caused by for instance a bad layout, long change-over times, unreliable suppliers,

quality problems, etc... In the JIT philosophy, decreasing lot-sizes is the first step towards

improving logistical performance, the ultimate aim being stockless production. This is often done

with the help of a technique called Single Minute Exchange of Die (SMED), also referred to as Quick Changeover. A schematic overview of JIT cycle processes is shown in figure VII.

Figure VII JIT, a process of continuous improvement (Brevé, 1993)

At several places where the JIT-philosophy has been implemented, it may be supported by Kanban (Brevé, 1993). A Kanban system is a control system developed by Toyota on which basis, via a set of circulating cards, short-term-material-supply and production-control is regulated. Kanban by itself is just a pull-system for the flow of goods which does not lead to improvements. Benefits must be found in the JIT philosophy.

Theory of Constraints

The basic thought of the Theory of Constraints is to ‘make money’. In financial terms this is

expressed in aiming for a maximum net profit, maximal investment returns and money streams. In

reality only one or two aspects are taken into account (Brevé, 1993). In operational production

terms this is translated into financial objectives such as increasing throughput (value added),

reducing inventory (non value added) and reducing exploitation cost (money needed to keep the

money making machine going). The TOC philosophy states that bottlenecks deserve all the attention: an hour lost at a bottleneck is an hour lost forever. Idling of a bottleneck resulting from delays or disruptions in the supply is prevented by using (safety-) buffers in front of the bottleneck. Production control software has been developed under the name of Optimized Production Technology. In this software production priorities and production capacity are simultaneously monitored and an algorithm takes decisions on priorities. The planning structure is shown in figure VIII.

Figure VIII Structure of OPT software