Improving Overall Equipment Effectiveness of the C/D production line

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Improving Overall Equipment

Effectiveness of the C/D production

line

Master thesis Technology Management

By Frank Beverdam

S1802712

f.j.beverdam@student.rug.nl

August 2010

Scania Production Meppel

Supervisor: Ing. H. Loijenga MBA

Department: Maintenance and facilities

University of Groningen

1st supervisor: Dr. Ir. H. van de Water

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Master Thesis – Frank Beverdam 2

Preface

This report is the representation of my final research project for the Technology Management masters degree program at the University of Groningen. I conducted this research project at Scania Production Meppel in the Netherlands. Scania Production Meppel is responsible for the painting of plastic cab and chassis parts, which are delivered to Scania’s European truck factories in Zwolle, Angers (France) and Södertalje (Sweden). During an internship of five months, I carried out an investigation into the area of Overall Equipment Effectiveness. This research project has been conducted with the help of many people; I would like to take this opportunity to show my appreciation to those who helped me to finish this research successfully.

First I would like to thank all the people of Scania Production Meppel who helped me with this project. Special thanks to Henk Loijenga for his guidance and the opportunity he gave me to perform this research. I also want to thank Stefan Broeknellis and Kees Haspels of Ijssel Technologie for their support during this research project.

Next to this, at the university I would like to show my appreciation to my supervisor Hen van de Water for all his comments, his guidance and his constructive criticism. Similar appreciation goes to my second supervisor Robert Rozier for helping me to bring this project to a successful ending.

Last but not least I want to thank my family and Renate for all their support during my final research project and study.

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Management summary

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Abbreviations

C Cab

CV Coefficient of variation

CONWIP Constant work in process

D Deflector

OEE Overall Equipment Effectiveness I&R Inspection and repair

HV High variability

MV Moderate variability

LV Low variability

SPS Scania Production System

TPM Total Productive Maintenance

TQM Total Quality Management

T0 Raw process time

T0* Ideal raw process time

WIP Work in process

W0 Critical WIP level

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1. Company description

This chapter provides a description of Scania production Meppel on basis of three aspects. Paragraph 1.1 will elaborate on the history of the company to create an understanding about their background. Paragraph 1.2 will addresses the strategic orientation of Scania. Their strategic orientation provides insight the aspects that are for the company important on the longer term. The third paragraph 1.3 will describe the Scania Production System (SPS), which is implemented by Scania CV AB in all the production units. SPS is representation of how Scania aims to organize their production. By introducing these aspects a general understanding about Scania and their way of producing should be created.

1.1 History

From 1964 till 2002 a cabin factory of Scania was located in Meppel. The cabin factory delivered complete truck cabins to the assembly plant in Zwolle. In 1993 a discussion started to invest in the cabin production in order to increase automation of the welding and painting processes. However, the investment had to made on two different locations, because another cabin factory was located in Sweden. To invest one time, Scania decided to centralize the production of cabins on one locations, this location became Sweden. The production of cabins stopped at Meppel in 2002 and resulted into the closure of the cabin factory, in which 600 employees were assigned. These employees have been transferred to the assembly plant in Zwolle.

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1.2 Strategy

The strategy of Scania Production Meppel is described within a strategic platform, which is defined over two years. The strategic platform also elaborates upon success factors, strategic actions, and key performance’s indicators, which used to make the strategy more specific, applicable, and measurable. In order to give an overall description of the strategic platform, the elements strategy and success factors will be highlighted.

The strategy of Scania Production Meppel is divided in two parts:

1. Producing painted parts with minimum environmental impact, right quality and delivery reliability within an efficient and flexible process.

2. Being a full component production unit as part of the Scania global production network.

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1.3 Scania Production System

In 1995 Scania approached Toyota to acquire information about their production system in which waste reduction has been of great importance. When contact was made, seven employees of Scania visited several production locations of Toyota in America. The visit resulted into fruitful insights for a new manufacturing system, in which lean manufacturing was of great importance. After a number of pilot projects, lean manufacturing has been implemented as a new structured way of thinking and working within all production units of Scania. This lean manufacturing system is called ‘Scania Production System’ (SPS) and is depicted in figure 1. SPS can be interpreted as an adapted version of the Toyota Production System for Scania.

Figure 1: Scania Production System.

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Master Thesis – Frank Beverdam 9 inventory, waiting time, unnecessary motion, defective products, and surplus process steps; the extra waste ‘unused capabilities’ is defined by Scania. The elimination of waste is considered essential, because it leads among others towards an increase in efficiency and flexibility, reduction of costs, and continuous improvement.

The floor of the house stands for Scania’s standardized working methods, and by means of these methods the specified philosophies should be brought into practice. The standardized working methods provide a consistent framework for performing work and for illuminating opportunities for making improvements in work procedures. The framework consists of six elements: work methods, takt time, balanced workload, smooth flow, visualisation, and actual information. The first element is the work method, which describes the current best way of completing a particular task. The task is performed the current way until a new better way is found to perform the task. The second element is takt time and is defined as the maximum interval between completion of consecutive units of a product (Miltenburg, 2001). In its purest sense takt time is used to produce exactly what customers will consume. The takt time of the production line by Scania is determined by dividing working time by the demand of trucks. The third element is a balanced workload, which is an important aspect for optimal utilization of workstations within a production line. For example, if workload is considered for the assembly of trucks, than complicated trucks with four axes enter alternatively the production line with more simplified trucks with only two axes. This results in a balanced workload for the workstations of line. The fourth element is smooth flow, which is created by a one-piece flow of the product through the system. In one-piece flow production, products pass or move along in the production process independently until it is completed and ready to be shipped to a customer. The fifth element is called visualisation, and this element is created because every employee should be able to notice whether a normal or abnormal situation occurs. Analysis of abnormal situations can help to improve the normal situation described within the standards. The last element of the framework is called actual information, which is presented by the Andon system. The Andon system provides information about the current status of the planning.

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Master Thesis – Frank Beverdam 10 The roof of the house stands for continuous improvement and is applicable within the normal situation. The normal situation is characterized by standardized working methods, which reflects the best current ways to perform activities. After a while particular working methods will be outdated and wastes can be discovered. Continuous improvement should lead to new and better working methods, which in turn become new standards for the normal situation. One way Scania simulates continuous improvement is by Kaizen improvement teams. Kaizen furnishes the dynamism of continuous improvement and the human motivation of encouraging individuals to take part in designing and managing their own jobs (Nicholas, 1998). Team leaders and team members of production will make part of the Kaizen improvement teams, because they are able identify and or rectify the actual problems.

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2. Research design

This chapter will describe the purpose, approach and guidelines of this investigation. Before doing this, paragraph 2.1 will elaborate on the subject of the investigation ‘Overall Equipment Effectiveness’ (OEE), which was introduced by Nakajima in the 1980s. By providing the aim of the OEE performance measurement system and describing the measuring method a general understanding about the subject will be created. In addition, paragraph 2.2 will address the problem context, in which the problem indicated by Scania will be introduced. Based on the problem context an appropriate methodology has been chosen for solving the indicated problem. Paragraph 2.3 will describe the applied methodology. Next to this, paragraph 2.4 will elaborate on the focus area, in which a specific choice will made to investigate one of the three manufacturing aspects. These manufacturing aspects have been introduced in the first paragraph 2.1. In addition, the problem statement will be described in paragraph 2.5, which is derived from the problem context and focus area. Within the problem statement the research objective and research question of this investigation will be discussed. The last paragraph 2.6 will address the sub-questions that are needed to answer the research question.

2.1 Overall equipment effectiveness

As noted by Fleischer et al. (2006), the competitiveness of manufacturing companies depends on the availability and productivity of their production facilities. In addition, Huang et al. (2003) state that due to intense global competition, companies are striving to improve and optimize their productivity in order to remain competitive. According to Muchiri and Pintelon (2008) the above situation has led to a need for a rigorously defined performance measurement system that was able to take into account different important elements of productivity in a manufacturing process. Measuring the performance of a manufacturing process provides information concerning the status of the process and enables decisions to be made concerning the adjustment of settings or actions to improve performance (Ron and Rooda, 2006). A key performance measure in mass-production environments is the Overall Equipment Effectiveness (OEE). OEE was introduced by Nakajima (1989) in the context of Total Productive Maintenance (TPM) and is directed towards equipment/machines. The aim of OEE measurement and analysis is to reduce the equipment losses to zero, which supports the improvement of equipment effectiveness and thereby its productivity. The potential losses are divided into six major categories, which affect the overall performance of the equipment, namely (Nakajima, 1989):

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by defective products;

• Set-up and adjustment losses are defined as time losses resulting from downtime and defective products that occur when production of one item ends and the equipment is adjusted to meet the requirements of another item;

• Idling and minor stop losses occur when the production is interrupted by a temporary malfunction or when a machine is idling;

• Reduced speed losses refer to the difference between equipment design speed and actual operating speed;

• Quality defects and reworks are losses in quality caused by malfunctioning of production equipment;

• Reduced yield losses occur during the early stages of production from machine start up to stabilisation.

The first two losses are known as down time loss and are used to calculate the availability of a machine. The third and fourth are speed losses that determine the performance efficiency and the final two losses are considered to be losses due to defects in the products. OEE is generally measured in terms of these six losses, as is illustrated in figure 2. These losses are functions of availability, performance efficiency and quality rate of the machine, production line or factory (Ljungberg, 1998).

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According to Ron and Rooda (2006) the description given by Nakajima (1989) is directed towards equipment, but OEE is impacted greatly by factors beyond the equipment itself, including the operator, recipe, facilities, material (input items) availability, scheduling requirements, etc. As this may result in OEE values influenced by factors beyond the equipment itself, a distinction can be made between stand-alone equipment and integrated equipment. OEE is directed towards equipment integrated in a manufacturing environment.

Next to this, Nakajima (1989) introduced ideal values for the OEE components, they are: • Availability in excess of 90 percent;

• Performance efficiency in excess of 95 percent; • Quality in excess of 99 percent.

Such levels of availability, performance and quality would result in an OEE of approximately 85 percent. The literature regarding appropriate levels of availability, performance and quality is far from clear (Dal et al., 2000). In fact several different opinions would appear to exist regarding the value of acceptable OEE performance. Kotze (1993) states that an OEE figure of greater than 50 percent is more realistic and therefore more useful as an acceptable target. Ericsson (1997) reports that acceptable OEE performance can vary between 30 percent and 80 percent. Further research (Ljungberg, 1998) reports OEE figures of between 60 percent and 75 percent respectively. In a comparison of values regarding each of the elements of OEE, Ljungberg (1998) reports that the mean percentage of OEE across the sampled cases, was 55 percent. Using the same source of data, the mean availability figure was 80 percent. This value approaches the standard suggested by Nakajima, that an availability of 90 percent would yield world-class performance. The average performance efficiency was 68 percent; however, this research (Ljungberg, 1998) discriminates between the losses due to idling and losses due to minor stoppages, the majority of losses being attributed to the latter. Ljungberg (1998) indicates that most companies performed over 70 percent, with one achieving 95 percent, the standard set by Nakajima (1988). The final component of OEE to be reported by Ljungberg (1998) was quality, with an average value of 99 percent. Again this coincides with the standard suggested by Nakajima (1989).

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measure has also number of disadvantages. These disadvantages have been noticed by the author of this investigation and will be discussed next. At first, by multiplying the manufacturing aspects availability, performance efficiency and quality rate, the valuable information of the three aspects will be captured in one single number. The separate manufacturing aspects provide more insight for driving plant improvement activities than the multiplication of the manufacturing aspects. Next to this, the multiplication of the manufacturing aspects could provide a biased view of the situation. The reason for this are causal relationships between the manufacturing aspects. Consider for example quality rate and performance efficiency. When rework needs to be performed in order to upgrade some products, it leads towards the loss of effective capacity. As a consequence, performance efficiency will decrease, because less effective capacity is available for the production of new products, due to the rework of the other products.

2.2 Problem context

Scania measures their manufacturing performance with the metric overall equipment effectiveness (OEE). Muchiri and Pintelon (2008) define OEE as a quantitative metric, which identifies and measures losses of important aspects of manufacturing. The OEE measure has been elaborated on in the previous paragraph 2.1. The OEE is for Scania of strategic importance, because the company strives for operational excellence. The OEE contributes towards operation excellence in the following way; the identification and measurement of losses of manufacturing complemented with the Scania Production System, in which continuous improvement is key, supports the increase in productivity. As a consequence, factors like quality, price and delivery reliability will be more competitive, due to focus on manufacturing aspects as availability, performance efficiency and quality rate.

The manufacturing performance at Scania is point of consideration. More specific, in the year 2009 the average OEE of the C/D production line has been calculated upon 62%. The C/D production line is the most important production line of Scania, because 80% of all the painted parts are being processed by this line. The target for the OEE has been set by Scania upon 80% in their strategic platform. Within the previous paragraph the discussion about target setting for the OEE have been highlighted. However, target setting will be dependent on every companies specific production environment and production capabilities. As result, the gap between Scania’s actual manufacturing performance and target has been the motive for this investigation.

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Master Thesis – Frank Beverdam 15 of the production line should to be further improved, otherwise capacity problems could occur. Second, the current equipment of the C/D production line has a high capital value, due to the automated painting processes and use of modern production technologies. The high capital value of the line makes the improvement of equipment effectiveness for the company interesting. Next to this, when the company is able to improve productivity of by optimizing their current manufacturing performance it can produce the amount of units within less operating time. This results in cost reduction due to the use of fewer resources.

2.3 Methodology

In order to structure this investigation a suitable methodology for problem solving is needed. As explained in the problem context there exists a gap between Scania’s manufacturing performance and their predefined target. This implies an unwanted difference between the existing manufacturing system and desirable manufacturing system. The unwanted difference between an existing and desirable system is introduced by De Leeuw (2002) as a management problem. A systematic methodology for approaching management problems is the DOV-method of De Leeuw (2002). The aim of the DOV-method is to optimize organizational performance and consist of three phases, which are graphically shown in figure 3.

Figure 3: DOV-method De Leeuw (2002).

The starting point for the application of the DOV-method is a management problem or problem situation. A problem situation is any situation, which is for management of a company reason to strive for improvement or innovation (De Leeuw, 2002). Within a problem situation goals of stakeholders regarding the system of interest can be unitary, diverging, or coercive (Jackson, 2003). The DOV-method is applicable in a problem situation where the goals of stakeholders are unitary or diverging (De Leeuw, 2002). In the situation of Scania 5 stakeholders have been identified, which have an interest in the system under consideration. The system under consideration has been defined as the C/D production line. The stakeholders are the managers of production, maintenance and facility manager, and managing director of Scania. All stakeholders acknowledge the problem situation, in which manufacturing performance is beneath the predefined target. As a consequence, it can be concluded that the stakeholders have unitary vision regarding the C/D production line. Next to this, Scania’s strategic platform confirms the agreement regarding the goal of the system. As result, DOV-method of De Leeuw (2002) will be applicable in the situation of Scania.

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Master Thesis – Frank Beverdam 16 The first step of the methodology is conducting a diagnosis, in which a vague problem situation will be transformed into a well described organizational problem. This forms the starting point for the design phase. The design phase comprises the translation of the diagnosed problem into concrete solutions. The translation should be performed by setting the requirements of the desired system. The last phase of the DOV-method is the change phase, in which the designed solutions will be implemented. It comprises the translation of a design into a concrete system that approaches the desired situation

The change phase of the DOV-method is not part of this investigation. Due to the time limitation of the investigation the actual implementation will be performed by Scania. In order to support the actual implementation of the designed solutions, implementation issue and requirements will be considered within the change phase of this investigation. In short, the change of the DOV-method is not excluded from the investigation, but will be outlined differently.

2.4 Focus area

The OEE identifies and measures losses of three manufacturing aspects. Due to the time limitation of this investigation, it is chosen to concentrate on one manufacturing aspect, which declares to high extend the actual performance of the OEE. In order to focus upon one manufacturing aspect an analysis has been performed regarding the OEE and pertaining aspects over a period of six months. The formula’s that are used by Scania to calculated the OEE are presented in appendix 1. The results of the analysis, which leads towards the choice for one of the aspects, will be described next.

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OEE October 2009 - March 2010

0,0% 20,0% 40,0% 60,0% 80,0% 100,0% 1 -1 0 -2 0 0 9 1 5 -1 0 -2 0 0 9 2 9 -1 0 -2 0 0 9 1 2 -1 1 -2 0 0 9 2 6 -1 1 -2 0 0 9 1 0 -1 2 -2 0 0 9 2 4 -1 2 -2 0 0 9 7 -1 -2 0 1 0 2 1 -1 -2 0 1 0 4 -2 -2 0 1 0 1 8 -2 -2 0 1 0 4 -3 -2 0 1 0 1 8 -3 -2 0 1 0 Date P e rc e n ta g e OEE Target Figure 4: OEE of C/D production line.

From the above graph can be concluded that the OEE is structural beneath the target of 80%. This can be underpinned with the average of 68,6%, which is calculated over the specified time range. The variation of the OEE can be described by means of the standard deviation. Standard deviation is according to Montgomery and Runger (2007) defined as the positive square root of the variance and is the most widely used measure of variability. The standard deviation of the OEE is calculated upon 8,1%. In order to interpret the standard deviation, the coefficient of variation (CV) should be determined. The CV is defined by Hopp and Spearman (2008) as relative measure of variation and can be calculated by dividing the standard deviation through the average. The CV of the OEE has been determined on 0,12 (8,1 / 68,6). Hopp and Spearman (2008) defined three classes of variability namely: low variability (LV), moderate variability (MV), and high variability (HV). According to Hopp and Spearman (2008) a random variable has low variability if its CV is less than 0,75. As result, the OEE of the C/D production line has been assigned towards the first variability class.

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Master Thesis – Frank Beverdam 18 Variabels of OEE 0,0% 20,0% 40,0% 60,0% 80,0% 100,0% 120,0% 1 -1 0 -2 0 0 9 1 5 -1 0 -2 0 0 9 2 9 -1 0 -2 0 0 9 1 2 -1 1 -2 0 0 9 2 6 -1 1 -2 0 0 9 1 0 -1 2 -2 0 0 9 2 4 -1 2 -2 0 0 9 7 -1 -2 0 1 0 2 1 -1 -2 0 1 0 4 -2 -2 0 1 0 1 8 -2 -2 0 1 0 4 -3 -2 0 1 0 1 8 -3 -2 0 1 0 Date P e rc e n ta g e _Quality Performance Availability

Figure 5: Manufacturing aspects of the OEE.

When figure 5 is observed, it can be concluded that quality is the most constant factor. With ‘constant’ is mend that the aspect quality approaches the maximum value of 100% most often in contradiction towards the other manufacturing aspects. Conversely to quality, performance is the most fluctuating factor. To elaborate in more detail upon the aspects of the OEE, table 1 presents the statistics: average, standard deviation and CV.

Statistics Availability Performance Quality

Average 90,9% 83,1% 91,0%

Standard deviation 6,6% 8,5% 4,2%

Coefficient of variation (CV) 0,073 0,10 0,046

Table 1: Statistics of the variables which determine OEE

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2.5 Problem statement

According to De Leeuw (2002) a problem statement consists of an research objective and research question. The research objective represents the objective of the investigation, whereas the research question describes the knowledge needed to achieve the objective. Within this paragraph the research objective and research question will be introduced, and have been derived from the previous paragraphs.

Based on the analysis in the focus area, it is chosen in this investigation to concentrate on the manufacturing aspect performance efficiency. According to Nakajima (1989) world class manufacturing is obtained when a company approaches an OEE of 85%. In order to reach this ideal situation, production should achieve a performance efficiency level of 95%. Assuming that the objectives concerning availability (90%) and quality rate (99%) have been reached. The specified level of performance efficiency can be seen as a benchmark and indicates the room for improvement. In addition, So (1989) states that within a repetitive manufacturing environment, a very small increase in efficiency can lead to a very substantial amount of savings. The statement of So (1989) is applicable in the situation of Scania, because Scania’s manufacturing environment is characterized as repetitive. Next to this, the costs one hour of production has been estimated by finance department on the € 5000,-. This leaded towards the following research objective:

Improve the performance efficiency of the C/D production line in order increase overall equipment effectiveness.

To improve the performance efficiency of the C/D production line it is important to understand the way Scania measures their performance efficiency. Figure 6 depicts their measuring method and the method will be elaborated on underneath the figure.

Formula 1:

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100 min % = × time Operating time operating Net efficiency e Performanc Formula 2:

Formula 3:

Operating

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Planned

production

time

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min

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−

Down

time

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Figure 6: Measuring method of Scania for performance efficiency.

The first component to calculated performance efficiency is net operating time and represents the minimum time to produce a specific number of products. Net operating time is a multiplication between the amount of produced products and takt time. The first factor, amount of produced products represents the actual production volume. The actual production volume is expressed in skids and include rerun skids. These skids contain

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Takt

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Master Thesis – Frank Beverdam 20 products that had to traverse the production line for a second time, due to deviations of the product apropos quality specifications. The second factor, takt time represents the pace at which the C/D production line produces. The second component for the calculation of performance efficiency is operating time. This components represents the actual time, which was needed to produce the specific amount of products. Operating time is calculated by subtracting down time form the planned production time. Planned production time is defined by Scania as the difference between the shift time and planned downtime. Planned downtime includes all the planned downtime effects as operator breaks, planned maintenance, and deliberation of production. In contrast to planned downtime, down time are the unplanned time losses, due to technical malfunction of the installation. The unplanned time losses are added during the day and result in factor down time.

When the measuring method for performance efficiency of Scania is compared with literature about this subject, it turns out that the current way of measuring by Scania suits the description given in the literature. Figure 7 provides the description given by Muchiri and Pintelon (2008) about the measurement of performance efficiency. The description given by Muchiri and Pintelon (2008) is also confirmed by Ron and Rooda (2006), Badiger and Gandhinathan (2008), and Nakajima (1989), who introduced OEE in the context of Total preventive maintenance. Formula 1:

( )

100 units output Actual x (h) time cycle l Theoretica % = × h time Operating efficiency e Performanc

Formula 2:

Operating

time

(

min

)

=

Planned

production

time

( )

h

−

Down

time

( )

h

Figure 7: Measure method described in literature for performance efficiency.

From the above figure can be concluded that the minimum time for producing the actual number of products is divided by the actual time, which was needed to produce the number of products.

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Master Thesis – Frank Beverdam 21 When the formulas in figure 6 are taken into consideration, operating time is determined over the total production volume. For a thorough analysis the excessive operating time should be considered per production unit. This is the reason why the actual cycle time of C/D production line will be investigated. Cycle time is according to Hopp and Spearman (2008) defined as the average time from release of a job at the beginning of the routing until it reaches an inventory point at the end of the routing. In other words, the time a part or product spends as work in process (WIP). Within the definition of Hopp and Spearman (2008) cycle time includes the average time losses of the production line. As result, the actual cycle time of the C/D production line incorporates these time losses, which influence the operating time. This leads towards to following research question:

How should the actual cycle time be reduced in order to increase performance efficiency of the C/D production line?

According to Hopp and Spearman (2008) production systems cycle time can be broken down into the following components: (1) Move time, (2) Queue time, (3) Setup time, (4) Process time, (5) Wait-to-batch time, (6) Wait-in-batch time, (7) Wait-to-match time.

(1) Move time is the time jobs spend being moved from the previous workstation. (2) Queue time is the time jobs spend waiting for processing at the station or to be moved to the next station. (3) Setup time is the time a job spends waiting for the station to be set up. (4) Process time is the time jobs are actually being worked on at the station. (5) Wait-to-batch time is the time jobs spend waiting to form a batch for either processing or moving, and (6) wait-in-batch time is the average time a part spends in a batch waiting its turn on a machine. Finally, (7) wait-to-match time occurs at assembly stations when components wait for their mates to allow the assembly operation to occur.

Hopp and Spearman (2008) made the following remark about the two cycle time components; in most production systems, we have seen that actual process and move times are a small fraction (5 to 10 percent) of total cycle time. Lines for which these terms dominate are probably very efficient with little opportunity for improvement. For inefficient lines, the major leverage lies in the other components of cycle time. More specific, Hopp and Spearman (2008) state that queue time is frequently the largest component of cycle time for inefficient lines.

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Master Thesis – Frank Beverdam 22 quantitative as well by qualitative factors. These possible factors will be discussed in the next paragraph.

2.6 Sub- questions

In the previous paragraph the research objective and research question have been introduced for this investigation. In order to answer the research question, sub-questions have been formulated for each phase of the DOV-method. As result, the phases are structured by sub-questions, which contribute towards realization of the objective of this investigation. The sub-questions per phase for this investigation are:

Diagnosis:

1) How can the production process of the C/D line be defined?

With this sub-question a general understanding of the production process will be created. By elaborating on the different process steps the production process will be introduced.

2) How can the cycle time for the C/D production line be defined?

With sub-question 2 insight will be created into the cycle time of the C/D production line. When the actual cycle time is compared with the minimum cycle time, the component queue time can be distracted.

3) Which factors cause the amount of queue time for the C/D production line?

With this question insight is created into the factors, which declare to high extent the current amount of queue time. Based on appropriate literature possible factors have been indicated, which could influence the amount of queue time in the situation of Scania. Two main factors have been distinguished and will be introduced next.

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Master Thesis – Frank Beverdam 23 not registered. In many cases, the minor chronic losses are regarded as something normal and the awareness of their impact on production output is not prevalent.

The second big loss is defined as reduced speed losses. Reduced speed losses refer to the difference between equipment design and actual operating speed. At the current, the net operating time is calculated on takt time of 94 seconds. The takt time of the first process steps of line are set on 94 seconds. The reason for this is that the C/D line have been designed to operate at a takt time of 94 seconds. As result, reduced speed losses will be excluded from this investigation.

The second factor has been introduced by Hopp and Spearman (2008) concerns work in process (WIP) of a production line. The authors state that reducing cycle time implies reducing WIP, whilst provided throughput remains constant. Hence, large queues are an indication of opportunities for reducing cycle time, as well as WIP.

Design:

4) What are the possibilities to improve the identified factors?

Within this sub-question the desired situation will be investigated. This will result in concrete requirements for the desired system. In addition, the requirements of the desired system will guide the design of new solutions for the influencing factors upon the amount of queue time.

Change:

5) How could these solutions be implemented at Scania production Meppel?

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3. Diagnosis

The diagnosis will elaborate on three sub-questions of the research design to transform the vague problem situation into a well described organization problem. The first sub-question will describe the production process of the C/D production line. In order to perform a thorough analysis, insight should be created into the various process steps of the line and their specific characteristics as for example the takt time. Paragraph 3.1 will describe these aspects. The second sub-question of the diagnosis will address the cycle time of the C/D production line. In order to distract the component queue time, the minimum cycle time and the actual cycle time have to be determined. The difference between the minimum and actual cycle time will indicate the amount of queue time. Paragraph 3.2 will describe this second sub-question. The third sub-question of the diagnosis will elaborate on the influencing factors of the component queue time. The queue time needs to be decreased to reduce the actual cycle time. When the factors that influence the amount of queue time have been identified, solutions for improvement can be created. Paragraph 3.3 will describe this third sub-question. Each paragraph will end with a brief conclusion about the most important finding.

3.1 How can the production process of the C/D line be defined?

This paragraph will introduce the production process of the C/D production line. The first section 3.1.1 will address the parts, which are being painted by the line. Next to this, it will elaborate on the transportation method of the parts by the production line. The second section 3.1.2 will describe the process steps of the C/D production line. One important characteristic is the takt time per process step. The reason for this is that the subsequent paragraph will use the takt time of each process step to determine the minimum cycle time. The last section 3.1.3 provides a brief summary with most important findings.

3.1.1 Painted truck parts

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Master Thesis – Frank Beverdam 25 side spoilers. The C/D production line has at least to paint C module parts for every produced truck. 70% of each produced truck contains D module parts. For all individual parts, different types can be distinguished. The customer order determines the truck configuration and part types that have to be processed for a particular truck. As result, different part configurations are being processed on the C/D production line.

Figure 8 (a & b): Truck parts.

Figure 2 A Figure 2 B

Part groups Colour Module Number Description

Cab module parts Yellow C 1,2 Corner parts

Deflector module parts Purple C 3 Upper grill

Rare line module parts Green C 4 Shielding net

Underline module parts Blue C 5 Lower grill

C 6 Sun visor

D 7 Roof spoiler

D 8 Side roof spoiler

D 9 Side spoiler

Table 2: legend of figure 8 A & B.

In order to paint the different parts, skids are being used to suspend and transfer the C and D module parts. Module C parts can only be suspended and transferred by C skids and module D parts can only be suspended and transferred by D skids. In addition, M skids are being used to suspend and transfer the grill parts (upper, lower grill and shielding net) of two trucks. The grill parts are components of module C and are suspended on M skids when they have to be painted metallic. The grill parts of 70% of all the produced trucks are painted metallic.

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Master Thesis – Frank Beverdam 26 the near future. Based on this information an installation is developed, which was able to process parts at takt time of 94 seconds. Nevertheless, some process steps produce at lower takt time. This will introduced in the description of multiple process steps.

3.1.2 Process steps

The C/D production line is able to paint parts with a topcoat or a metallic. This is realized by splitting the painting process up in two parallel lines namely line fraction T2 and T3. Parts that have to be painted metallic will only be processed on line fraction T2 and are first treated with a water base coat (WBC). This treatment takes place in WBC T2 and can only be performed in WBC T2. After painting the parts with a WBC, the parts have to be painted with a clear coat (CC). This treatment is performed in CC T2. Top coat can be painted on line fraction T3 as well as on line fraction T2. Line fraction T3 is only appropriate to paint parts with a top coat and this treatment is performed in Topcoat T3. With CC T2 it is also possible to paint parts with a topcoat, but when top coat is used, WBC T2 will not be used. Figure 9 on the next page shows the process overview of the C/D production line. Each step will be discussed next.

Loading T2 /T3:

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Figure 9: Process overview C/D production line

Legend:

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Master Thesis – Frank Beverdam 28 Powerwash W2:

After loading the skids with particular parts, the loaded skids are transferred to the powerwash, in which the parts are cleaned. At first, the loaded skids are sprayed with a mixture of water and soap under pressure, after which they are blown off with hot air. The powerwash provides place to 12 skids, which are continuously being transferred by a conveyor operating at a constant speed. The speed of the conveyor is controlled as such that every 94 seconds a skids leaves the powerwash and another can enter.

Drying W2:

To ensure that all water is evaporated from the parts, the loaded skids will run through a dryer. Within the dryer, a maximum number of 15 skids can be heated till 90 degrees Celsius. The time of drying is controlled by a takt time of 94 seconds for each position. When the takt time is expired every skid is transferred one position further, which means that every 94 seconds a skid leaves the dryer.

Night Buffer: W2, T2, and T3:

Night buffers are used to store the loaded skids, which are in process previous to the night buffers. The operators of the second shift will start the ‘buffer breakdown function’ at the end of their working time. From this moment on, supply of new skids to the production line will be stopped. The loaded skids, which are in production, will be processed until the last skid has reached the night buffer. The first night buffer W2 has capacity to store 30 loaded skids, which is satisfactory to store all skids of the previous processes. The second night buffer T2 has a capacity of 39 skids and the third night buffer T3 has a capacity of 33 skids. The advantage of night buffers is that production can start immediately from this point on the next morning. Otherwise, it takes a few hours to fill the production line with loaded skids.

When production starts the next morning, the night buffers will be utilized completely and the breakdown function is turned off. Under normal production conditions, new skids will arrive at the time the buffers are almost completely used. During the day the loaded skids will run through the night buffer at a pace determined by the subsequent processes. As result, the number of stored skids will fluctuate during the day, which is a characteristic of a flexible buffer.

Cooling W2:

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Master Thesis – Frank Beverdam 29 capacity to store 8 skids and the time of cooling is controlled by a takt time of 94 seconds per position. When the takt time is expired every skid will be transferred to the next position.

Buffer T2 and T3:

After the cooling process, the C/D production line splits up in two parallel painting lines namely line fraction T2 and T3. A buffer is located before each painting line, in which the loaded skids for T2 and T3 are temporally stored. Both buffers have capacity to store 12 skids and supply their own painting line. The painting lines determine the pace at which the buffers supply the skids.

Top / water based coat T2:

WBC T2 consists of two painting booths, in which the same painting activities are performed. At the current, WBC T2 is only used to paint parts with a water based coat. In the near future, WBC T2 will also be used to paint parts with a top based coat, but this is still in an experimental stage. The painting process of WBC T2 is divided into 7 sub processes. At first, the painting process starts with the inspection of parts loaded on the skid. After that, the parts will be ionized, which results in neutral charged parts. Neutral charged parts do not attract any dust. In the third step, parts will be painted in the first booth by two robots on both sides. One robot is located in front of the skid and the other robot is located behind the skid. The painting process takes places under predefined conditions. Temperature, humidity and air flow are regulated within the painting booths to obtain best painting results. The fourth step in the process is called flash off. During flash off the paint, which is just sprayed on the parts, gets 170 seconds time for flowing and evaporation. After that, the parts will be painted for the second time in step five, and this result in one combined layer of paint. The reason for this is that steps three and five are performed close after each other whereby the paint has insufficient time to dry, which is called wet-in-wet. Next to this, both painting booths are identical and operate under the same conditions. However, the settings of robots do differ between the two booths. The sixth step in the process is a second inspection, which takes places every 15 minutes to guarantee the quality of the painted parts. When irregularities occur in the paint, the process will be stopped until the problem is resolved. The last step in the process is flash off 2 and has the same function as described previously. The cycle time of top / water based coat T2 is controlled with takt time and is set on 170 seconds.

Drying: Top/ WBC T2, Top/Clear coat T2, and Topcoat T3:

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Master Thesis – Frank Beverdam 30 ranges. Parts which are being processed on line fraction T2 will be dried twice for a smaller time period than parts that are being processed by line fraction T3. These parts are dried once for a longer time period. The drying time is depends on the number of positions of a particular dryer, because the takt time of each dryer is set on 170 seconds.

Cooling: Top / WBC T2, Top/Clear coat T2, and Topcoat T3:

After each drying process the parts have to be cooled down till 19 degrees Celsius. This can be necessary because an additional painting layer has to be applied or operators of the subsequent process step have to work with the parts. The cooling time of the above specified cooling units (Top/WBC T2, etc.) is regulated with a takt time of 170 seconds, but differentiates per cooling unit. The reason for this is that number of positions differ per cooling units.

Top / clear coat T2:

CC T2 consists also of two painting booths, in which the same painting activities are performed. Within CC T2, top coat and clear coat can be used for painting parts. When top coat is used, WBC T2 will not be used, and the loaded skids will just run through it. However, when the parts are treated in WBC T2 with a water based coat (metallic), then the parts have to be painted in CC T 2 with a clear coat. The painting process of CC T2 consists of 5 steps for top coat as well for clear coat. At first, the parts will be painted with a top coat or a clear coat in the first painting booth. After that, the parts will go to flash off, which is the second step in the process. The third step is a second treatment of the parts with a top coat or clear coat in painting booth number two. The fourth step in the process is an inspection, which takes places every 15 minutes, where after the second flash off will occur as step five.

The cycle time of top / clear coat T2 is controlled with takt time, which is set upon 170 seconds.

Top coat T3:

Buffer T3 stores and supplies skids, which have to be processed on Top coat T3. Line fraction T3 is only appropriate to paint parts with a top coat. Top coat T3 consists of two paining booths, in which the same activities are performed by the robots. For Top coat T3 the same process steps can be distinguished as for WBC T2. In addition, the cycle time is also controlled by takt time, which is set upon 170 seconds per position.

Inspection and repair T2 / T3:

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Master Thesis – Frank Beverdam 31 lines of inspection and repair. The skids are alternatively assigned towards one the inspection and repair lines. Figure 10 shows the 3 parallel lines. Each line has a takt time of 255 seconds per station. When the inspection and repairs activities have been performed the stream of skids will be combined again. To aggregate the skids each line delivers alternatively a skid every 255 seconds. The sequence of arrival will be the sequence of departure. This results in an overall takt time of 85 seconds (255 / 3 = 85) for inspection and repair.

Figure 10: Parallel lines of Inspection and repair.

Each inspection and repair line is divided into 8 stations. The first station is assigned for inspecting the incoming parts. When irregularities occur in the paint; they are made visible for the next stations by means of a product assessment form. This form indicates the type of flaws and their locations. The next five stations are assigned to repair the irregularities in paint indicated by the form. The repair activities start with polishing the specified location of the flaw, where after the flaw is recovered by adding extra paint. When irregularities in paint cannot be repaired in time, the part will be removed from the skid. The skid with the other parts will proceed. The repair activities concerning a removed part will be performed outside the line. The subsequent process ‘unloading’ will be informed when a part is recovered. Depending on the kind of flaw, repair could also reject parts, which results in repainting (rerun) or destruction of the part. The last two stations of each inspection and repair line perform a quality check of the recovered parts, after which the loaded skids go to unloading.

Unloading T2 / T3:

After inspection and repair, the loaded skids will go to unloading. The unloading area is divided into 6 workstations. The first three workstations are assigned to unload module C parts and the last three workstations are assigned to unload module D parts. At each workstation the module C or D parts are taken off the skid and are packed into temporarily buffer or box. The parts that packed into a temporarily buffer, require additional assembly activities, which are performed a part of the C/D production line. The cab corners and sun

Arrivals of skids Departures of skids

Inspection & repair line 1 (takt time 255 sec. per station)

Inspection & repair line 2 (takt time 255 sec. per station)

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Master Thesis – Frank Beverdam 32 visors are packed into a box according to the required chassis sequence of the assembly plants in Zwolle, Angers (France) and Södertälje (Sweden). The reason for this is that the assembly plants have to be provided with the parts according to their chassis sequence. The chassis sequence of an assembly plant represents the order of trucks on line and is determined for each plant within their planning. The chassis sequence of the assembly plants has been processed by the department logistics of Scania Production Meppel into the skid program for the C/D production line. This means that the sequence of skids on the C/D production line confirms the chassis sequence of one the assembly plants.

However, when batching occurs, module C and D parts with the same colour requirements are released after each other onto the production line. This results in reduced operating costs for the painting lines, but changes the confirmation between sequence of Scania Production Meppel and the assembly plants. Operators at different unloading stations have to recover the chassis sequence for cab corners and sun visors while they are packing. For the rest of the parts that temporarily buffered, assembly employees instead of the unloading operators have to recover the chassis sequence. The cycle time of unloading is control with takt time, which is set upon 85 seconds per position.

Skid buffer T2 / T3:

When the skids are unloaded, the empty skids will be transferred by a conveyor to the empty skid buffer. The empty skid buffer stores the skids separately per type into their predefined rows. The empty skid buffer counts six rows, of which five rows are used to store C, D or M skids. Of the five rows, 2 rows are assigned for C skids, which is also the case for D skids. The remaining row is assigned for the M skids. Next to this, the maximum storage capacity per row is 7 skids. The sixth row is used as a by carrier for skid types of the U/R production line.

3.1.3 Conclusion

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Master Thesis – Frank Beverdam 33 The parts will be packed into a box or temporarily stored in a buffer. The parts that are stored in a buffer require assembly activities after which they are packed and shipped to the assembly plants of Scania.

The C and D module parts are suspended on skids, by which they traverse the production line. The loaded skids are transported by a closed conveyor system through the production line. The conveyor system is organized in such a way that a continuous flow of skids is established. The continuous flow of the C/D production line is established and controlled by takt time. The C/D production line has been designed to operate at a takt time of 94 seconds. However, the takt time differentiates per process step. Table 3 presents an overview of the takt time per process step.

Line fraction Process step Takt time (sec)

T2 / T3 (a) Loading 94

T2 / T3 (a) Powerwash (*) -

T2 / T3 (a) Drying W2 94

T2 / T3 (a) Night buffer W2 (**) -

T2 / T3 (a) Cooling W2 94

T2 Buffer T2 -

T2 Top / water based coat T2 170

T2 Top/ WBC drying T2 170

T2 Top/ WBC cooling T2 170

T2 Top / clear coat T2 170

T2 Top / clear coat drying T2 170 T2 Top / clear coat cooling T2 170

T2 Night buffer T2 -

T3 Buffer T3 -

T3 Top coat T3 170

T3 Top coat drying T3 170

T3 Night buffer T3 -

T3 Top coat cooling T3 170

T2 / T3 (b) Inspection & repair 85

T2 / T3 (b) Unloading 85

T2 / T3 (b) Empty skid buffer - Table 3: Overview takt time per process step.

(*) The powerwash is not regulated by takt time. The speed of the conveyor is controlled as such that every 94 seconds a skids leaves the powerwash.

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3.2 How can the cycle time of C/D production line be defined?

This paragraph will elaborate on the cycle time of the C/D production line. Section 3.2.1 will describe the raw process time of the C/D production line. The raw process time is used in this investigation to indicate the minimum cycle of the C/D production line. In addition, section 3.2.2 will address the actual cycle time of the C/D production line. The difference between the actual and minimum cycle time will indicate the amount queue time of the C/D production line and will be described in section 3.2.3. In order to reduce the actual cycle of the C/D production line the queue time should be decreased. The last section 3.2.4 will provide a summary of the most important findings.

3.2.1 Raw process time

Hopp and Spearman (2008) define the raw process time (T0) of a production line as the sum of the long-term average process times of each workstation in the line. The authors emphasize to consider the length of the planning horizon, when deciding what to include in the ‘average’ process times. Over the long term, T0 should include infrequent random and planned outages, while over a shorter term it should include only the more frequent delays. Random outages are defined by Hopp and Spearman (2008) as outages, that can occur right in the middle of a job, whether we want them to or not. Random outages, for example power outages, are regarded as machine breakdowns, due to their similar effects on the behaviour of production lines. Planned outages are stoppages that occur between, rather than during jobs. Planned outages, for example setups, represent downtime that will inevitably occur, but for which we have some control as to exactly when.

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Master Thesis – Frank Beverdam 35 to exclude waiting time from T0 and use T0*. As a consequence, the difference between T0* and actual cycle time will give insight in the component queue time, which is included in the actual cycle time.

To determine T0*, the closed conveyor system of the C/D production line has been investigated. The reason for this is that C/D production line is highly automated and skids are being transferred by the conveyor system. The conveyor system consists of 164 single conveyors with exception of the conveyors of the empty skid buffer. Of these 164 conveyors, two types can be distinguished namely, speed and takt conveyors. Speed conveyors are used for transportation purposes, and are not restricted to a predefined move time. Speed conveyors run with a constant speed and deliver a skid, only when the next position of the subsequent conveyor is available. When the next position of the subsequent conveyor is not available, the current conveyor will wait. The second type of conveyor is a takt conveyor, which is in contrast to a speed conveyor restricted to a predefined move time. A takt conveyor regulates the move time of a loaded skid that undergoes an operation within one of the process steps. As a consequence, every skid will be transferred to the next position of the operation, when the takt time is expired. The time of each operation has to be controlled well, because little variation in move time has impact upon the quality of the product. If the operation flash off is considered as example, a longer move time will result in a longer flowing and evaporation time. A longer flowing and evaporation time will abrogate the wed-in-wed effect during the painting process. This leads towards a too rough structure of the paint. The only operation, which is regulated by speed conveyors, is the operation powerwash. However, the moving time of a skid to the subsequent position is controlled in such a way that it is comparable with the predefined move time of takt conveyor.

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Master Thesis – Frank Beverdam 36 The data set (N) is derived from the database PDM, which registers the arrival and departure moments of every skid per conveyor. The sample size per conveyor is compiled out of two consecutive production days randomly chosen in the month May and/or June.

M = number of speed conveyors.

i

N = number of movements for speed conveyor i ( i = 1, 2, …, M) in sample.

i j

D

= departure time of speed conveyor i for jth ( j = 1,2, …, Ni) movement.

i j

T

= move time of speed conveyor i for jth movement.

i j

T

=

D

ij - 1 − i j

D

* 0

T

= ideal raw process time *

0 ^

T = approximation of T0* for speed conveyor i. * 0 ^ T = ji j T Min

Figure 11: Mathematical summary approximation T0* of speed conveyor.

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Master Thesis – Frank Beverdam 37 M = number of speed conveyors.

i

N = number of time measurements for moving a skid 1 position of speed conveyor i ( i = 1, 2, …, M).

i j

T

= move time of speed conveyor i for jth ( j = 1,2, .., Ni) measurement.

i j

T

Min

= minimum move time of speed conveyor i over j.

i

P = number of storage positions for speed conveyor i. *

0 ^

T = approximation of T0* for speed conveyor i. * 0 ^ T = _ji j T Min x P_i

Figure 12: Mathematical summary of the approximation of T0* for a speed conveyor.

To determine T0* for a takt conveyor, three steps have been taken. At first, the takt time of each takt conveyor has been collected. Table 3 of section 3.1.3 provides an overview of the takt time per process step. By relating a takt conveyor towards a particular process step the takt time could be distracted. Second, the number of storage positions of each takt conveyor have been collected. Third, the takt time of each takt conveyor is multiplied with the number of storage positions of the conveyor. This resulted in the raw process time T0* for each takt conveyor. Figure 13 provides a mathematical representation of the calculation. In addition, appendix 2 gives an overview of the raw process times per conveyor of each process step.

M = number of takt conveyors I = takt conveyor i ( i = 1,2...,M).

i

T = takt time of takt conveyor I .

i

P = number of storage positions of takt conveyor I . *

, 0 ^

i

T

= approximation of T0* for takt conveyor i. * , 0 ^ i

T

= T_i x P_i

Figure 13: Mathematical summary determination T0* of takt conveyor.

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Master Thesis – Frank Beverdam 38 A small remark has to be made about the summation of raw process time per process step and line fractions. The process step inspection and repair is divided into three parallel lines as indicated by figure 10. Each line has the same raw process time. This is the reason why the raw process time of one single line is only incorporated into the T0* of the C/D production line. Next to this, the painting process of the C/D production line is also divided in two parallel painting lines. The analysis demonstrated that T0* for line fraction T2 was higher than T0* for line fraction T3. Because the T0* of only one painting line could be incorporates into the T0* of the C/D production line, it has been chosen to incorporate T0* of line fraction T2. The reason for this is to create a realistic picture. When T0* of line fraction T3 was incorporated into the T0* of the C/D production line, skids which traverse painting line T2 would always exceed the T0* of the C/D production line.

Figure 14 provides a mathematical representation of the calculation of T0* for the C/D production line. T0* is calculated upon 263,9 minutes, which is 4,4 hours. Table 4, on the following page depicts the raw process time per process step, line fraction and for the C/D production line.

( )

i j

g

T = raw process time of conveyor i ( i = 1,2,…,M) pertaining to process step j ( j = 1,2,...,N) of line fraction g ( g = 1,2,...,Q).

( )

g j

T = raw process time of process step j ( j = 1,2,…,N) pertaining to line fraction g ( g = 1,2,...,Q).

( )

g _j T =

∑

( )

= M i i j g T 1 j = 1,2,...,N g = 1,2...,Q.

( )

g

T

= raw process time of line fraction g.

( )

g

T

=

∑

( )

= N j j

g

T

1 g = 1,2,...,Q. * 0

T

= ideal raw process time of the C/D production line. * 0

T

=

∑

( )

= Q g g T 1 g

≠

3 (line fraction T3)

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Line fraction Process step Conveyor numbers T0* (min)

T2 / T3 (a) Loading 2930, 2940, 1100, 1110, 1120 9,9

T2 / T3 (a) Powerwash 1140, 1150, 1160, 1170, 1190 22,2

T2 / T3 (a) Drying W2 1200, 1210, 1220, 1230 24,4

T2 / T3 (a) Night Buffer W2 1240, 1250, 1260, 1280, 1290, 1300, 1320, 1330, 1340 6,0

T2 / T3 (a) Cooling W2 1350, 1360, 1370, 1380, 1400 13,8 Sub total 76,3 T2 Buffer T2 1410, 1420, 1430, 1440, 1450 13,6 T2 WBC T2 1460, 1470, 1480, 1490, 1500, 1510, 1520 20,0 T2 Drying / Cooling T2 1530, 1540, 1550, 1560, 1570, 1580, 1590, 1600, 1610 13,9 T2 CC T2 1620, 1630, 1640, 1650, 1660, 1670, 1680 17,5 T2 Drying T2 1700, 1710, 1720, 1730, 1740 38,2 T2 Cooling T2 1750, 1760, 1770, 1780 28,1 T2 Night Buffer T2 1800, 1810, 1820, 1840, 1850, 1860, 1880, 1890, 1900, 1910 7,7 Sub total 139,0 T3 Buffer T3 2000, 2010, 2020, 2040, 2050, 2060, 2070, 2080 9,2 T3 Topcoat T3 2090, 2100, 2110, 2120, 2130, 2140, 2150 17,2 T3 Drying T3 2160, 2170, 2180, 2190, 2200, 2220, 2230, 2240 69,6 T3 Buffer T3 2260, 2270 T3 Night Buffer T3 2280, 2300, 2310, 2330, 2340, 2350, 2370, 2380, 2390 6,8 T3 Cooling T3 2400, 2410, 2420, 2430 20,8 T3 Sequence buffer T3 2450, 2460, 2470, 2480 2,8 Sub total 126,4 T2 / T3 (b) Sequence buffer 2490, 2500, 2520, 2590, 2530 2,6

T2 / T3 (b) Inspection & Repair B2 2535, 2540, 2545, 2550, 2555 34,0 T2 / T3 (b) Inspection & Repair B3 2605, 2610, 2615, 2620, 2625 34,0 T2 / T3 (b) Inspection & Repair B4 2665, 2670, 2675, 2680, 2685 34,0

T2 / T3 (b) Unloading 2570, 2640, 2700, 2710, 0880, 2810, 2820 12,0

Sub total 48,6 Total 263,9 Table 4: T0* per production step.

3.2.2 Actual cycle time

Improving Overall Equipment Effectiveness of the C/D production line