Delft University of Technology
FACULTY MECHANICAL, MARITIME AND MATERIALS ENGINEERING
Department Marine and Transport Technology Mekelweg 2 2628 CD Delft the Netherlands Phone +31 (0)15-2782889 Fax +31 (0)15-2781397 www.mtt.tudelft.nl
This report consists of 169 pages and 14 appendices. It may only be reproduced literally and as a whole. For commercial purposes only with written authorization of Delft University of Technology. Requests for consult are only taken into consideration under the condition that the applicant denies all legal rights on liabilities concerning the contents of the advice.
Specialization: e.g. Transport Engineering and Logistics Report number: 2015.TEL.7967
Title: Improving the purchase, nesting
and order release process for a batch shop production process
Author: L.C.A. Sturm
Title (in Dutch) verbetering van het inkoop, nesten en order vrijgifte process voor een batch shop productie process
Assignment: Master thesis
Confidential: yes (until: 15-9-2020) Initiator (university): Prof. dr. ir. G. Lodewijks
Initiator (company): J.S. Geelhuysen Msc. (Fokker Aerostructures, Papendrecht) Supervisor: dr. W.W.A. Beelearts van Blokland
Delft University of Technology
FACULTY OF MECHANICAL, MARITIME AND MATERIALS ENGINEERING
Department of Marine and Transport Technology Mekelweg 2 2628 CD Delft the Netherlands Phone +31 (0)15-2782889 Fax +31 (0)15-2781397 www.mtt.tudelft.nl
Student: L.C.A. Sturm (1309455) Assignment type: Master thesis Professor (TUD): Prof. dr. ir. G. Lodewijks Creditpoints (EC): 35
Supervisor (TUD): Dr. W.W.A. Beelaerts
van Blokland Specialization: TEL/PEL Supervisor 1 (Fokker): J.S. Geelhuysen Msc. Report number: 2015.TEL.7967 Supervisor 2 (Fokker): Ir. J.P.M. Remmerswaal Confidential: Yes
Subject: Improving the purchase, nesting and order release process for a batch shop production process.
Problem
The sheet metal department at Fokker Aerostructures produces a large variety of low demand products used within different assembly programs. The production process is operated in a batch job style of operations because this large product variety. The first process in the production process is a milling stage in which the general geometrics of the products are cut from sheet material. Multiple production orders are cut from the same metal sheets in order to reduce the material losses at this stage. Production order are thereby released in batches and can be released prior to their planned release date. This batched release of production orders increases the material efficiency of the milling process but has detrimental effects on the effectiveness of the downstream batch job production process. The problem in the current process is that large batches of orders are released at once to the batch shop style of production. This increases the level of work in progress and worsens the on time performance of the production process.
The main problem is to identify which process design changes can improve the performance of the purchase and order release process which in turn can increase the effectiveness of the downstream production process.
Aim of this research
The scope of this research lies in the processes that are performed before the orders are released to the production floor and does not include the physical production process. The scope of this research is limited to the process that are performed before production orders are released to the production floor. This includes the purchase process for raw sheet material and nesting process in which custom milling patterns are created.
The aim of this research is to analyze the current purchase and order release system and determine possible future process designs. Additionally the effects of using different sheet dimensions is analyzed. The future alternatives should be able to increase the effectiveness of the production process while simultaneously produce products for at least the same production costs. The proposed future process design should be able to increase the material efficiency, reduce the disturbance on the on-time performance. Furthermore it should be able to reduce the average size of batched order released due to combined nesting and milling.
Delft University of Technology
FACULTY OF MECHANICAL, MARITIME AND MATERIALS ENGINEERING
Department of Marine and Transport Technology Mekelweg 2 2628 CD Delft the Netherlands Phone +31 (0)15-2782889 Fax +31 (0)15-2781397 www.mtt.tudelft.nl Approach
The first step in the solution approach is to study the current production process on a functional level in order to uncover its specific constrains and process limitations. Thereafter a literature review on lean manufacturing is performed in order to provide a handhold for an additional process analysis. Furthermore this review is used to formulate alternative future process designs and process requirements. The alternative future states are thereafter compared using a simulation model on these process requirements.
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Preface
This master thesis is the result of my Master of Science graduate research at Fokker Aerostructures in Papendrecht, The Netherlands. I have chosen the direction of Mechanical Engineering at Delft University of Technology, with the specialization Transport Engineering and Logistics. The assignment was to investigate the effects of using different sheet dimensions and the use possible alternative process designs on the material efficiency and effectiveness of the downstream production process. First of all I would like to thank Wouter Beelaerts van Blokland, Jeroen Geelhuysen and Hans Remmerswaal for their support and helpful advice during this research. I also would like to thank Prof. Dr. Ir. G. Lodewijks and Dr. M.A. Oey for their participation in the graduation committee. Furthermore I would like to thank Joop Baart, Edwin Penning and Itamar Veneman for their help and support during this research thesis. Especially Joop Baart has been very helpful in uncovering the working of the ERP system
Additionally I would like to thank my family and Madelon for their continued support during my life and this graduation project. I would especially like to thank my father Charles and I hope that the speed of his recovery continuous to amaze me.
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Summary
At the sheet metal department at Fokker Aerostructures a high variety of low demand sheet metal products are produced for use in different aerospace assembly programs. The production process operates in a batch shop style of operations in order to cope with the high-variety and low-volume nature of the product mix. In order to ensure that the products are delivered on time, the release of production orders is planned by an ERP system and production order receive a planned start date. It is the task of the production planner to ensure that the different orders are released as close to this planned start date as possible. This task is however made more difficult because of batched release of production orders. Production orders are released in batches in order to be able to cut multiple order from the same sheet at the milling process, which is the first step in the production process. Orders are released in batches in order to reduce the material losses. This batched release does however reduce the effectiveness of the production process by increasing the variation of start of the production process and thereby increasing the level of work in progress.
The objective of this master thesis is determine the effects of using different sheet metal dimensions in the milling process on both the incurred material costs and the effectiveness of the downstream production process. Furthermore this research investigate if different functional process designs are able to improve the effectiveness the purchase and order release process. The scope of the research is limited to the process that takes place before the milling process step.
The production process is analyzed using a combination of Value Stream Mapping and the ‘PROPER’ model from the Delft Systems Approach. These analyses are performed, in combination with a quantitative and statistical analysis, in order to uncover the operational constrains and limitations of the current order release process. From these analyses it has become apparent that in the current functional design, sheets are purchased based on an expected material usage as calculated by the ERP system. The expected material usage is an overestimation of the actual material requirements. After receiving the different materials a custom milling pattern is created in the nesting process. In the nesting process the actual material requirements are uncovered. Due to the overestimation of material usage additional production orders are released in nesting process to use up the excess ordered sheet material. Therefore two alternative future states are designed, based on lean manufacturing principles, in order to mitigate the negative effects of this material use overestimation.
The different future state process designs are tested using a simulated model in order to analyze their effects the performance of the purchase and order release process. As part of the simulation model the nesting process is simulated using a greedy 2D bin packing algorithm.
First the current functional design is modeled in which the influence of alternative sets of sheet dimensions are tested. Moreover in this first model the influence of different purchase and order release process parameters is put forward. In the second future state model, named feedback control, the nesting process is performed just before purchase orders are created. Thereby in this future state it is possible to determine the size of the purchase order based on the actual material usage. In the last future state, Kanban control for purchase orders is introduced in combination with using a two bin inventory of raw sheet material. Again in this model the purchase orders are based on the actual material usage instead of the overestimation of material usage as calculated by the ERP system in the current operation.
The material efficiency of the different functional designs is judged based on the total material costs as calculated by the simulation model. The effectiveness of the different future states is determined
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based on the variation in the OTP of the order release process. Additionally the effectiveness is judge based on the average number of production orders that are released in a batch.
From the simulation model it can be concluded that by changing the sheet dimensions of 20 out of a total of 86 material groups, a cost reduction of 12.500 euro can be achieved. Furthermore it can be concluded that the purchase and order release process is improved the most when implementing a Kanban control method for the replenishing of sheet material. Both the material costs as well as the effectiveness of the production process is improved the most when implementing this future state design. Variation in the OTP of the order release process can be reduced by an estimated 16%. Furthermore Kanban control reduces the average number of production order released per batch by 10%. Additionally from the simulation model it has become apparent that in the current production process design at least 6.3% of the production volume is comprised out of ineffective work release caused by the overestimation of material usage. This ineffective work release comprises out of the increase of production order batch sizes and the additional excessive early release of production orders. This ineffective work is released in order to use up the sheets that are ordered in excess of the actual material requirements. Both in feedback and Kanban control this overestimation of material usage is remove which in turn reduces the level of overproduction and increases the effectiveness of the downstream production process. The implementation of this control method is however only partially feasible because of the limitation in available storage space. Feedback control offers a good alternative for those material groups that cannot be controlled via Kanban. This functional process designs offers the same material efficiency with a slightly lesser increase of process effectiveness. This future state model offers similar results for the reduction of overproduction and an equal decrease of average number of orders that are released in a batch. The variation in OTP of this future state model is however reduced by 3% in comparison to the current process design.
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Summary (in Dutch)
Bij de plaatwerk afdeling bij Fokker Aerostructures wordt een hoge verscheidenheid van lage volume plaatwerk producten geproduceerd voor gebruik in de verschillende aerospace assemblage programma's. Het productieproces werkt in een batch shop stijl van processen om om te kunnen gaan met de hoge-variëteit en low-volume aard van de productie mix. Om ervoor te zorgen dat de producten op tijd geleverd, wordt de vrijgiften van productieorders gepland door een ERP-systeem en ontvangen de verschillende productieorders een geplande startdatum. Het is de taak van de productie planners om de verschillende orders zo dicht mogelijke bij deze geplande startdatum vrij te geven. Deze taak wordt echter bemoeilijkt doordat productieorders in batches worden vrijgegeven. De vrijgiften gebeurt in batches om er voor te kunnen zorgen dat meerdere orders van uit hetzelfde plaat materiaal kunnen worden gesneden in het freesproces. Het frees proces is de eerste stap in het productieproces van de verschillende orders. In dit proces worden meerdere producten uit dezelfde platen gesneden om materiaal verliezen te besparen. Deze batchwijze vrijgave heeft echter een negatieve effect of de effectiviteit van het downstream productie proces. Dit komt omdat er extra verstoringen ontstaan in het begin van het productie proces en omdat er een hoger Work in Progress niveau ontstaat.
Het doel van deze scriptie is om het effect van het gebruik van verschillende plaat afmeting in het frees proces op de materiaal efficiency en de effectiviteit van het downstream productieproces te bepalen. Bovendien heeft deze scriptie als doel te onderzoeken of dat alternatieve functionele proces ontwerpen in staat zijn om de effectiviteit van het aankoop en order vrijgiften proces te verbeteren. De scope van dit onderzoek is gelimiteerd tot de processen die plaatsvinden vóór het frees proces. Het productieproces wordt geanalyseerd met behulp van een combinatie van Value Stream Mapping en de 'PROPER' model van de Delft Systems Approach. Deze analyses worden uitgevoerd, in combinatie met een kwantitatieve en statistische analyse, met het doel om de operationele beperkingen en nadelen van het huidige ordervrijgiften proces onthullen. Uit deze analyse is gebleken dat in het huidige functioneel ontwerp, platen worden gekocht op basis van een verwacht materiaal gebruik berekend door het ERP-systeem. Het verwachte gebruik materiaal is een overschatting van de werkelijke materiële behoefte. Na ontvangst van de verschillende materialen wordt een aangepaste freespatroon gemaakt in het nest proces. In dit nest proces wordt de werkelijke materiaal behoefte bepaald. Als gevolg van de overschatting van materiaalgebruik extra worden productieorders vrijgegeven in nesten proces om de excessief bestelde plaatmateriaal op te gebruiken.
Om de negatieve gevolgen dan deze materiaal overschatting te voorkomen zijn twee alternatieve future state model ontworpen. Deze alternatieve functionele proces ontwerpen zijn gebaseerd op lean manufacturing principes. De verschillende toekomstige future state modellen worden getest met behulp van een simulatiemodel om hun invloed op de prestaties van het inkoop en ordervrijgiften proces te analyseren. Als onderdeel van het simulatiemodel wordt het nestproces gesimuleerd met behulp van een greedy 2D bin packing-algoritme.
Eerst wordt de current state model gesimuleerd, hierbij wordt de invloed van alternatieve sets van plaatafmetingen bepaald. Bovendien wordt in dit eerste model de invloed van verschillende inkoop en ordervrijgiften parameters bepaald.
In het tweede functionele ontwerp, feedback control, wordt het nest proces naar voren verplaatst naar vóór het inkoop proces. Hierdoor wordt de bestelhoeveelheid gebaseerd op de werkelijke materiaal behoefte en wordt er niet langer gebruik gemaakt van een (over)schatting van materiaal gebruik.
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In de laatste future state wordt een Kanban control ingevoerd in combinatie met een two bin inventaris van ruw plaat materiaal. Hierdoor worden inkoop orders pas gemaakt op het moment dat de platen daadwerkelijk zijn gebruikt. Ook in dit model worden inkoop order gebaseerd op het werkelijke materiaalgebruik in plaats van de (over)schatting zoals in het huidige proces.
De materiaalefficiëntie van de verschillende functionele proces ontwerpen wordt beoordeeld op basis van totale materiaal kosten zoals berekend door het simulatie model. De effectiviteit van de verschillende alternatieve future states wordt beoordeeld op basis van de variatie in de OTP van het ordervrijgiften proces. Bovendien wordt de effectiviteit bepaald op basis van het gemiddeld aantal productie orders dat in een batch wordt vrijgegeven.
Uit het simulatiemodel kan worden geconcludeerd dat door het veranderen van de plaatafmetingen van 20 uit in totaal 86 materiaalgroepen, een kostenreductie van 12,500 euro worden bereikt. Verder kan worden geconcludeerd dat het aankoop en ordervrijgave proces het meest verbetert bij de invoering van een Kanban besturingswerkwijze voor het bijvullen van plaatmateriaal. Zowel de materiële kosten als de effectiviteit van het productieproces wordt het meest verbetert bij de invoering van deze future state. Die variatie in de OTP van het ordervrijgiften proces kan met een geschatte 10% worden verminderd. Bovendien vermindert Kanban control het gemiddeld aantal productie orders dat in een batch word vrijgegeven met 10% Bovendien is uit het simulatiemodel gebleken dat in het huidige productieproces ten minste 6,3% van het total productievolume bestaat uit ineffectief vrijgegeven werk als gevolg van de overschatting van materiaalgebruik. Dit ineffectieve werk bestaat uit de toename van de seriegrootte van de verschillende productieorders en de extra afgifte van te vroeg vrijgegeven werk. Dit ineffectieve werk wordt vrijgegeven om het te veel aan bestelde aantal platen, door overschatting van materiaalbehoefte, alsnog op te gebruiken. Zowel
feedback als Kanban control elimineren deze overschatting van materiaal gebruik. Dit zorgt er voor dat
in deze twee future state modellen er een afname is van overproductie en een daar aan gekoppelde verhoging van de effectiviteit van het downstream productieproces. De totale invoer van Kanban
control is echter niet mogelijk door beperkingen in de beschikbare opslagruimte voor plaat materiaal. Feedback control is een goed alternatief voor de materiaalgroepen welke niet via Kanban control
kunnen worden aangestuurd. Dit functionele procesontwerp biedt dezelfde materiaalefficiëntie met een iets geringer toename van de proceseffectiviteit. Deze future state biedt vergelijkbare resultaten voor de vermindering van overproductie en een gelijke afname van het gemiddeld aantal orders dat in een batch word vrijgegeven. De variatie in OTP van deze future state wordt echter verslechterd met 3% in vergelijking met het huidige proces ontwerp.
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Table of content
Preface ... iii
Summary ... iv
Summary (in Dutch) ... vi
1. Introduction ... 1
1.1. Fokker Technologies ... 1
1.2. Sheet metal department ... 3
1.3. Problem statement ... 13
1.4. Research objective and scope ... 15
1.5. Main research question and sub questions ... 15
1.6. Report structure ... 16
2. Research Design ... 16
2.1. Methodology ... 16
2.2. Lean manufacturing ... 25
2.3. Sub conclusion ... 32
2.4. Packing and cutting stock problem ... 32
2.5. Sub conclusion ... 37
2.6. Modelling ... 38
2.7. Sub conclusion ... 39
3. Process analysis ... 40
3.1. Value Stream Mapping for current state ... 40
3.2. Delft Systems Approach ... 43
3.3. Sub conclusion ... 46 3.4. Quantitative analysis ... 46 3.5. Sub conclusion ... 55 3.6. Statistical analysis ... 56 3.7. Sub conclusion ... 72 4. Modelling ... 72
4.1. Input and output of model ... 73
4.2. Functional design of model ... 74
4.3. Nesting model ... 81
4.4. Future state models ... 83
4.5. Sub-conclusion ... 86
5. Results ... 86
5.1. Verification ... 87
5.2. Validation ... 88
5.3. Alternative sheet dimensions only – Future state 1 ... 91
5.4. Feedback purchase control – Future State 2 ... 98
5.5. Kanban purchase control and safety stock – Future State 3 ... 101
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6. Conclusions ... 109
6.1. Main research question ... 109
6.2. Sub questions ... 110
7. Recommendations... 114
8. References ... 116
Appendix A: Scientific research paper ... 118
Appendix B: Fokker Aerostructures... 127
Appendix C: Strategic position of Sheet metal department ... 129
Appendix D: Future demand on Sheet metal department ... 130
Appendix E: Enterprise Resource Planning (ERP) ... 132
Appendix F: Scrap factor and expected material usage ... 143
Appendix G: Main reasons for variation in production start date ... 146
Appendix H: Main reasons for variation in throughput time ... 151
Appendix I: Typology of nesting problem ... 154
Appendix J: Lean manufacturing additional information ... 156
Appendix K: Supplementary process description ... 158
Appendix L: Future state functional model ... 162
Appendix M: Verification of nesting algorithm ... 165
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1. Introduction
A general introduction of Fokker Technologies is provided in this chapter. This introduction is used to provide context to this research objective and in order to clarify its relative importance. Furthermore in this chapter the research objective and problem statement of this master thesis are put forward. Additionally the research scope and the different research questions are explained. First the company Fokker Technologies is introduced in section 1.1. Thereafter the sheet metal department which is particular interest to this master thesis is presented in section 1.2. In this section particular emphasis is put on the rubber-pad forming flow which is at the heart of this master thesis. Thereafter the problem statement is presented in section 1.3. Fourth the research objective and research scope of this master thesis are presented in section 1.4. Thereafter the main questions is presented in section 1.5. Finally in section 1.6 the general structure of this report is clarified.
1.1. Fokker Technologies
Fokker Technologies has had a long history in aviation as an independent aircraft manufacturer. Until the bankruptcy in 1996, Fokker designed and produced its own aircraft. Since then Fokker Technologies has reinvented itself as a global specialist supplier. The company no longer operates as an aircraft integrator but has specialized itself as a supplier in design, development and manufacturing of aircraft parts. Nowadays the company operates in service to other aircraft manufacturers. Because of its experience as an aircraft integrator, Fokker Technologies is able to help aircraft manufacturers in all stages of the production and maintenance process. This unique mindset resulting from the company’s history has enabled Fokker technologies to become a leading aerospace supplier.
Presently Fokker Technologies is involved in the production process of 75 different aircraft types. These aircraft types are a mix of civil and defense aircraft. Customers of Fokker Technologies include all major aircraft integrators. Customers include but are not limited to Airbus, Boeing, Dassault, Gulfstream and Lockheed Martin. In 2013 Fokker Technologies generated a revenue stream of € 762 million with an operational result of €27 million. With 4,688 employees operating multiple production locations around the world, Fokker Technologies is truly a global aerospace supplier specialist.
In order to remain successful as top tier supplier Fokker Technologies has formulated its vision and goals for the year 2020, depicted in figure 1 on the next page. The 4 four main goals in order to remain a competitive top tier supplier are:
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2 1. Achieve a turnaround of €1 billion, to
guarantee a stable supply chain. 2. Increase Fokker’s global presence, to
create new business opportunities and access cheaper production locations. 3. Innovation as a source competitive
advantage, both in technical solutions and in innovative business concepts. 4. Customer focus, their success it’s the
companies own.
Fokker Technologies is divided into four separate business units, depicted in figure 2 on the next page; Fokker Elmo, Fokker Landing Gear, Fokker Services and Fokker Aerostructures.
Fokker Elmo is a specialist business unit in the design, manufacturing and support for the electrical wiring interconnection systems for aerospace and defense programs. The business unit has multiple locations around the world and employs around 1,700 people.
Fokker Landing Gears is a specialist business unit in the design, development, testing, production and maintenance repair and overhaul of landing gears. This business unit has one production location in the Netherlands and employs around 250 people.
Fokker Services is an integrated, knowledge based service provider that partners with owners and operators for continuous, competitive fleet operations. Maintaining and overhauling both Fokker as well as third party aircraft. This business unit operates on multiple locations around the world and employs around 850 people.
Fokker Aerostructures is a business unit that is specialized in the design, development and production of smart light weight aerostructures. It specializes in the production of empennages, fuselages and wing movables. This business unit has multiple production locations around the world and employs around 2,000 people.
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Figure 2, business unit of Fokker Technologies
1.2. Sheet metal department
The business unit Fokker Aerostructures1 is at the center of this master thesis and in this unit one
production process is of particular interest. This production process is the sheet metal production process. The sheet metal production department at Papendrecht transforms raw sheet metal products in lightweight aerostructures components. Within the sheet metal production process, metal sheets are transformed into shaped metal components by a number of conventional manufacturing techniques. To further clarify the sheet metal process, this process has been broken down in underlying process-steps in figure 3. 2
Figure 3, Different process flow in the sheet metal department
1
Readers are referred to appendix B for more detail on Fokker Aerostructures
2 In figure 3 above the flow of 90% of the produced components is displayed. The other 10% of products have so different
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The production process at the sheet metal department can be broken down into four main production flows. These flows can be separated from one another based on their corresponding routing, shared required production steps and product characteristics. These four main production flows are:
1. Large-size milling and Glare® construction; product flow in which large (3m+) aluminum sheets
are milled in stacks, chemically treated and stored individually in preparation for Glare® construction. The sheets are milled on a large milling table which is nearly (90 %+) exclusively
used for Glare® construction.
2. Profile milling and bending; product flow in which long narrow metal profiles are milled and bend into shape to form stringers. Stringers are long profiles that are used as longitudinal stiffeners of lightweight aero structures. The inbound metal profiles have been cut-to-size by the suppliers and only detailed milling and bending processes are required. After the milling and bending production step, the stringers go through a metal bonding step to form the backbone of the aero structure and are then coated in the next production department. 3. Stretch forming; product flow in which aluminum sheets are stretched over a mold to form
the exterior metal surface of different aerostructures. Most of the used metal sheets are brought in cut-to-size from the suppliers. Some smaller surfaces are cut-to-size by the small milling table at the sheet metal department itself. Generally after the stretching production step, the metal surfaces are checked for quality, reworked, chemically etched, chemically bonded with other components and are sub sequentially coated.
4. Rubber-pad forming; product flow that start when aluminum sheets are milled on the small milling table. After this milling process in which the shape of the product is defined, products follow two general routings. Either they follow their process through to the heat treatment and rubber pad forming process step or through the bottoming and roll forming process. The quality of the products is checked after these processes and shape adjustment are performed when need be. The products thereafter are chemically bonded and coated next department. The fourth product flow (Rubber-pad forming flow) is of particular interest to this research thesis and is examined in more detail next. The four described flows are separated as much as possible. The flows do however have interactions as there is some overlap in used resources and processes.
1.2.1. Rubber-pad forming flow
The sheet metal department produces a large variety of products required in the different assembly programs that are conducted in both Papendrecht and Hoogeveen. Just within the rubber-pad forming flow alone, 950+ different types of products for 40 different assembly and spare programs where
produced in 2014. Furthermore the different types of products that are produced by the rubber-pad forming flow follow variable routings through the sheet metal shop floor.
Because of this high-variety and low-volume production at the sheet metal department, the production process is best defined as a batch shop process. A batch shop is a standardized job shop that has a reasonable stable line of products produced in periodic batches to meet customer requirements or for inventory. (Case & Aquilano, 1995) It is a job shop with less variety in the product path flow and is characterized by product queues at different workstations and consequential long lead times. (Hayes & Wheelwright, 1984)(Brown & Mitchell, 1991, p. 907)
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The different workstations required in the production process are sub-divided into different production cells. This done in order to increase the flow through the production process. Production employees autonomously work in these production cells without direct supervision. Furthermore they have the ability to switch between the different cells. The workstations have been sub-divided based on the dominant product flows of the production processes. This in contrast to the traditional functional layout of a job shop, in which the workstations are grouped together based on their functional process.
The floor plan of the Sheet metal department is depicted in figure 4 below. The different workstations are grouped together based on the dominant routing of the different product flows. This is done in order to minimize the transport distance between sub sequential process steps. However the different product flows are not entirely lined out in this floor plan. This is because of constrains in the floor space and the immovability of heavy equipment. For instance the oven, used in the heat treatment process step, has been placed approximately 15 years ago and moving it is simply too costly and is therefore not lined up with dominant product flows. On the right side of figure 4 the four main production flows are laid over floor plan to illustrate product flow layout.
Figure 4, floor plan of sheet metal department
The production process is characterized as a batch and queue process in which order lie in wait in queues at the different work stations. Production employees daily receive a work schedule that stipulates in which sequence the different orders need to be handled. At the rubber-pad flow, orders are required to be handled in the sequence of the earliest planned processing date of that particular process step. However this rule is not set in stone and employees may deviate from the queuing discipline. This can be done when set-up times between orders can be reduces by following a particular sequence. This in turn improves the overall productivity but can negatively influence the service level. The process flow layout and sub-division of workstation in different production cells enables a high level of autonomy for production employees. On average a product has between seven and eight routing steps before it is completed.
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A number of lean manufacturing techniques have been implemented over the years in order to remain competitive. The production process operates on a Just-In-Time (JIT) basis. Therefore products are produced only when there is a demand for these products and are delivered just before they are requested. The JIT method is used by the ERP system to determine when and how many products need to be produced. By delivery products just before they are needed and in the right quantity, high inventory levels are no longer required which frees up financial resources. Apart from JIT other lean techniques such as for instance 5S are implemented in the production process. It has however proved difficult to fully implement lean manufacturing because of the high-variety low-volume nature of the process.
The different production cells used by the Rubber pad flow are operated in either one, two or three shifts. This depends on the capacity demand on the specific production cell. In general there is ample machine capacity available and worker capacity is the limiting factor. Production employees are cross-trained to enable them to switch between different production cells. This makes them able to cope the shifting production bottlenecks. The batch shop can therefore be characterized as a dual-resource-constrained batch shop.
Within a batch shop environment the planning of the different orders through the production process is one of the main difficulties it is operation. (Blazewicz, J. et al, 1996) In order to cope with this planning difficulty, order receive a planned throughput time and planned order release date. The planned throughput time and planned release date of orders is used to ensure that no product shortages arise. The planned throughput time is calculated by a mathematical model based on the expected required touch time and includes reservations for expected waiting times at every routing step. The average planned throughput time of orders in the rubber pad flow is approximately 27 working days. This long planned throughput time is mostly dependent on the reservations made for expected waiting times at the different work stations. 98,6%3 of the planned throughput time of orders
is made up of these waiting time reservations while on average only 6,2 hours is actual touch time! To keep track of all the different orders and the performance of the different production cells the ERP system records the order transactions between the different work stations. The time required by a production employee to record and administer these transaction is a non-value adding activity and needs to simplified as much as possible. Therefore at the sheet metal department employees are only required to record whenever they complete the process step of a production order. To further simplify the required accounting procedures a group wise remuneration per flow cell is used. Thereby the productivity of the process is determined on a weekly basis and on flow cell level instead of on a per production order level. This group wise remuneration is based on Overall Equipment Effectiveness (OEE) calculations. Since workforce capacity is the limiting factor in most flow cells a slightly adapted version called Overall Work Effectiveness (OWE) is used. In this performance metric the process effectiveness is split into three categories: Availability, Performance & Quality. The formula used in the calculation of the OWE of a process is presented below. Through this simple representations sources of waste are more easily identified and improvement actions can be quickly undertaken. Additionally
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many of the non-value but necessary activities are thereby removed from the process while still being able to provide useful process information.
𝑂𝑊𝐸 = 𝐴𝑣𝑎𝑖𝑙𝑎𝑏𝑖𝑙𝑖𝑡𝑦 ∗ 𝑃𝑒𝑟𝑓𝑜𝑟𝑚𝑎𝑛𝑐𝑒 ∗ 𝑄𝑢𝑎𝑙𝑖𝑡𝑦
A number of Key Performance Indicators (KPI) are used to measure and control the process. These KPI are used to ensure that products are delivered at the right quality and as close to their requested delivery date as possible.
The first indicator used in the control of the Rubber pad flow is quality centered. The NC-rate of Non-conformity rate is expressed as the total number of defects per 1000 production hours. Quality defects are a major source of waste in any production process and strict control is necessary to ensure customer satisfaction. The current NC-rate is one 1% which is extremely low given the high product variety and complex processes used.
The second KPI used at the rubber pad flow is the productivity of the different flow cells. Productivity of production employees is measured on a flow cell level and in a weekly cycle. Productivity is expressed as the percentage difference between the planned touch time and the actual number of production hours spend at that flow cell by production employees.
The final important KPIs used in the Rubber pad flow are the service level and on-time performance (OTP) of the production process. The service level of the production process is defined as the percentage of orders that are delivered at most one week after their planned delivery time. The
on-time performance of the rubber pad flow is defined as the percentage of orders that are delivered in
and around a week of their planned delivery date. At the sheet metal department the OTP is called the
On-Time Delivery or OTD. Both the service level and the on time performance measurement as used
by Fokker are presented in figure 5 below.
Figure 5, KPI viewer of Fokker to determine the OTP and service level
The OTP of the production process is determined by two disturbance on the timely production. First the OTP is affected by the difference between the planned and actual start date of orders. This difference is the called the On-time-Start or OTS of the process by Fokker. The second disturbance is the variation between the planned and actual throughput time of orders. This research thesis is centered on the OTS of order release and the processes that affect it. Therefore in this research thesis the production process is effectively cut up in two parts.
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The first part of the process is defined as the purchase and order release process. It performance is measured by Fokker according to the OTS metric. In this master thesis however the timely performance of this process is defined as the OTP of the order release process.
The second part of the production process is the ‘true’ or physical production process. This last part of the production system is not part of the scope of this master thesis and will therefore receive limited attention.
This research thesis is centered on the processes that precede the milling process and effect its timely performance and material efficiency. Therefore these processes are introduced in further detail in the next two paragraphs. First the raw material purchase and the production order release process are discussed. Thereafter the automated loading and handling system used by the milling table and the milling process itself are introduced in more detail.
1.2.1.1. Purchase and production order release process
Before orders are released to the production process, the production planner of the sheet metal department need to perform a number of operations to ensure their timely release. First of all raw sheet metal plate need to be purchased and delivered to the shop floor. Second the production orders themselves have to be released and a custom milling pattern needs to be provided. These two processes are introduced in more detail next. First the purchase process is explained in more detail and sequentially the main characteristics of the order release process are put forward.
Purchase orders
In 2014 a total of over eight thousand square meters of sheet materials was used to produce the different products. The total value of the used sheet metal was 459 thousand euros and 114 different types of sheet metal materials where used. The different types of materials used can differ from one another based on their thickness, specific alloy composition and type of base metal. All types of metal sheets are supplied by All Metal Services Ltd. (AMS). This British specialist supplier delivers high quality metal products to over 80 high-tech manufacturers worldwide. Because of limitations in the amount of storage room and the sheer number of different materials used, no safety stock of raw material is kept at Fokker.
Raw sheet material is ordered two weeks in advance to ensure the timely arrival of the material. This sub sequentially ensures the timely release of production orders. New purchase orders are created and send on a weekly basis and delivered to the production location two weeks later by truck.
Each different type of sheet material is ordered in a fixed standard sheet size per material type. A fixed standard sheet size per material type is used because of the way in which products and raw material are connected in the ERP system. The amount of sheets that are ordered is determined by the ERP system based on the future demand of that particular material type. The ERP system generates purchase orders on a lot-for-lot basis. This ordering technique uses a two week order interval. Readers are referred to appendix E for a more detailed explanation on this planning method.
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This estimate is based on a calculation which is based on the rectangular product formed by the maximum height and width of the product. This area is thereafter multiplied with a scrap factor which is used to relate the product dimensions to the dimensions of the metal sheet. A detail description on how the material usage is calculated by the ERP system is provided in appendix F.
The material requirements according to the ERP system are always an over-estimate of the true material requirements. It is however a necessary evil in order to ensure that products can always be cut from the available sheet material. It is the best estimate that is able to cope with the dimensional constraints of the used sheet size and limited information available. After receiving the raw sheet material, the final preparations for the release of production orders can be made.
Production orders release process
Production orders (PO) themselves are also planned using the lot-for-lot planning method. This planning method for production orders is explained in more detail in appendix E. The POs are planned with an order interval of either thirty, sixty or ninety calendar days. These relative short order intervals have been chosen in order to reduce inventory levels and increase the amount of manufacturing learning. The order interval is set based upon the standard costs and the size of product. The way in which this sub-division of order intervals is made is explained in more detail in appendix E.
Due to the use of the lot-for-lot planning method, POs have no fixed order quantity and there is no correlation between order quantities and sheet dimensions. This means that the material requirements of a single PO does not have to be in line with the sheet dimensions and that high levels of material waste can result. Moreover because of the low-volume nature of the department it is not possible to fully ‘fill’ a plate with one type of products. If one was to operate on this basis it would result in high inventory levels that cover more than a year’s worth of product demand.
In order to ensure that no product shortage arise, POs receive a planned delivery date, throughput time and planned start date to guide them through the production process. Production planners need to release POs as close to their planned start as possible in order to ensure that they are eventually delivered on time. However production planners are allowed to release batches of POs that use the same type of sheet material. This done in order to reduce the material waste at the milling process. By releasing multiple orders at the same moment it is possible to cut the orders from the same metal sheets and drastically reduce the material wastes. POs can be released a maximum of four weeks before their planned release date. This time period of early released is called the order coupling
window in this master thesis. The on time start of production orders is however reduced by this
batching of POs. In appendix G an example is presented to further clarify this batching in order release and its effects on OTP of the order release process. The nesting process is a specific variation of the general packing and cutting stock problem. The nesting is best defined as a combination of a
Multiple Identical Large Object Placement Problem (MILOPP) and Multiple Stock Size Cutting Stock Problem (MSSCSP). In appendix I a detail typological review of the nesting process is provided. After orders are released by the production planners, operation sheets are printed and the batch of POs in handed over to the nester. The nester in turn creates a cutting pattern or nest for the milling process. In this nest the different batched POs are placed on the same metal sheets in order to reduce material waste. The nester can alter the order quantity of the different POs somewhat in order to
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improve the material efficiency even further. Furthermore if space is still available he can request additional POs to be released by the production planner. The nester uses a software packages to help design the milling pattern and to determine the numerical control of the milling head. The software package that is used by the nester is the ASCO package by Siemens. Figure 6 below presents an example of a cutting pattern create by the nester.
Figure 6, example of milling pattern created in the nesting process
When the nests or cutting patterns are completed by the nester, the batched production orders are released to the milling process and the ‘real’ production process can start. The start of the ‘real’ production process is thereby not controlled by a release mechanism such as for instance CONWIP control. (Spearman M. et al. 1990) The process at the milling table itself is explained in more detail in the next paragraph.
1.2.1.2. Automated loading and milling process
The milling process at the sheet metal department is of particular interest to this research thesis. In order to further clarify this process a brief introduction to this process itself and the surrounding automated handling equipment is presented next. First the automated loading system is further explored including the operational constraints that are introduced by the system. Second the milling process itself is clarified in more detail.
Automated loading system
Metal sheets are currently delivered up on request to the department in two fixed sizes: Full- and quarter-sized plates.4 All Metal Services (AMS) delivers both sizes on a weekly basis. AMS hold the
material types in stock in different prime-stock dimensions that are different from the requested dimensions. Therefore the sheet are cut-to-size by AMS in the requested material dimensions prior to deliver.
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For the handling of the full-sized plates a custom transportation system is used. This transportation system or ‘cassette system’ has been designed to protect the metal sheets during transportation while simultaneously allowing for automated and easy handling by the loading system. The ‘cassette system’ is displayed in figure 7 below. When new full-size sheets are delivered to the sheet metal department the full ‘cassette’ is switched out for an empty ‘cassette’. The empty ‘cassette’ sequentially is returned to AMS and filled up in a weekly cycle. The full ‘cassette’ is immediately in place to be handled by the automated loading system and no additional handling is required. A maximum of two ‘cassettes’ are interchanged in a weekly cycle.
Figure 7, ‘cassette’ and automated loading system Figure 8, examples of material cut-outs and material scraps
Within the each box or ‘cassette’ there are a twelve slots which hold sheet stacks of a maximum of 16mm thickness. A maximum of 5 ‘cassettes’ can be placed in a row and be reached by the automated loading system. The slots can be moved from one ‘cassette’ to another in order to create an empty ‘cassette’ which can sub-sequentially changed over by a full ‘cassette’. Sheets inside the slots are not interchanged between slots at the moment. This could be done to for instance free up a slot by moving all sheets to one slot. When a plate is required by the milling process the automated handling equipment takes a slot out of the ‘cassette’ system, turns and opens it. Thereafter a moveable top-mounted vacuum pad table picks up the metal sheet and move it in place on the milling table. Once a sheet is on the milling table the entire plate needs to be used and cannot be moved back in to storage. This is because the vacuum pad table can only handle sheet that do not have milling cut-outs. The quarter-size plates do not use an automated handling and transport system. This size of plates is transported to Fokker on a pallet and stored in the general warehouse in the same weekly cycle. When these types of plates are requested they are moved from the general warehouse to the milling table by the logistic department. The ‘small’ plates are sub sequentially manually loaded on the milling table by the production employee and the milling process can start. Scraps from these plates are not saved as this would result in a warehouse full of odd shaped sheets.
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After the nester has generated a milling pattern or nest for the batched production orders, the operating sheets are picked up by the milling operator. The milling operator thereafter starts the ‘true’ production process. First the employee calls out the required sheet type from the automated loading system that is automatically loading on to the milling table. The milling table secures the sheets and stops it from moving by creating a vacuum from underneath. In figure 9 below the layout of pads that create this vacuum is displayed. Additionally the two milling heads are displayed on the right hand side of the figure.
Figure 9, Milling table including the vacuum pad layout
After loading the sheet the production employee does a final check to ensure that the right material type is loaded onto the milling table. Sequentially he downloads the custom milling program, which was created by the nester, onto the milling driver. Thereafter the actual milling process begins and the employees adjusts the milling speed in order to ensure that no cut-outs are flung form the milling table. He simultaneously completes the necessary paperwork while the milling process is running. After the milling process has finished the sheet scraps and product cut-outs are automatically conveyed from the milling table on a bed next to the milling table. This is displayed in figure 8 on the last page. The production employee thereafter sorts the different product cut-outs. Together with the operation sheet these products are moved to the intermediate storage area next to the milling table in anticipation to the deburring process. The sheets scraps are moved to a movable container next to the milling table and are eventually sold as metal scrap.
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1.3. Problem statement
The sheet metal department is under pressure to perform in a highly competitive global market. The financial performance and customer satisfaction are two of the most important parameters in order to remain a competitive business unit. The OTP of the entire production process is however affected by process constrains and difficulties in the order release process. In order to clarify these constrains and to be able to present the problem statement a short summary of the process difficulties is presented next. Thereafter the future challenge of the sheet metal department and the rubber pad flow in particular is put forward.
1.3.1. Current production process
The sheet metal department is not a core capability of Fokker but serves as a strategic asset.5
Management of the sheet metal department is constantly pressured to increase the efficiency of the production process of the sheet metal department. Both the efficiency of material use and the efficiency of production labor hours are under scrutiny in light of achieving competitive costs. Additionally the service level of the production process is one of the major KPIs used to judge the performance of the process. Late delivery of orders is disruptive for downstream production and assembly processes and can lead to costly productivity and time losses. Thereby the effectiveness of the production process is also under scrutiny by production management.
The sheet metal department operates in a batch shop type of operations. This type of operational control is characterized by long lead times and high work in progress levels. In the rubber pad flow the release of orders is ERP driven and controlled by a planned order release date. Production planners try to follow this planned release date as close as possible to ensure the timely delivery of orders. This process is however disrupted by operational constraints in the material storage, handling equipment and by the size of the used metal sheets.
Multiple orders are cut from the same metal sheet in order to reduce material waste. This means that multiple orders are released simultaneously to the shop floor. Because of this simulations release many orders are released in advance of their planned released date and a higher work in progress (WIP) level is incurred. Due to the batching of orders in sub sequential steps6, the effectiveness of the entire
production process is reduced by a higher WIP levels. This means that the service level is negatively affected by the batched release of production orders while the efficiency of labor hours increase. Furthermore the batched release complicates the use of WIP-control methods such as CONWIP. Different production control methods are explained in greater detail in section 2.2.
The batch shop operations of the department has ha relatively stable and long planning horizon in which orders are built to order. 7 This long planning horizon of more than a year’s worth of production
is characteristic of the aerospace and automotive industries. All production orders are customer driven and no products are made without a hard sales order. In addition to the long planning horizon in which the amount of requested products is known, the minimum sheet dimensions to produce the different
5
Readers are referred to appendix C for a detailed look at the strategic importance of the department
6
The negative effect of batching in different process steps is explained in more detail in section 2.1.3.
7
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products are known as well. Because of this stable product demand and knowledge of the product dimensions, the plate procurement of plate dimensions can be adapted according to the demand rate. Material types with higher demand or that are used by products with large dimensions can be purchased in large sizes. Low-volume and small products can be made from material types that are bought-in in smaller sizes.
The procurement method and the size of the material sheets have a direct effect on the controllability and deliverance reliability of the production process. Additionally the material costs incurred in the process are directly related to the size of the purchased material sheets. The sheets procurement method therefore needs to balance the efficiency of material use and the effectiveness of the production process.
1.3.2. The challenge for the sheet metal department
The sheet metal department in general and the rubber pad flow in particular is under pressure to manufacture products more cost-effective and with a higher delivery reliability. There is increased outside pressure to reduce the recurring costs of manufacturing and from low wage alternative production locations. This outside pressure incentivizes the department to look for ways of cutting costs and increasing the reliability of deliverance.
In the rubber pad forming flow the batched release of orders that increases the material efficiency of the milling process simultaneously reduces the effectiveness of the production process. The effectiveness of the production process is reduced since higher levels of work-in-progress caused by early release of orders reduce the control on the production process. Employees are able to deviate further from the maintained queuing discipline in order to increase their personal productivity. They are incentivized to deviate from the queuing discipline as the batching of particular orders can save them setup times. By reducing the necessary set up times they are able to increase their own productivity. This however increases the variations in throughput time of orders which is detrimental to the OTP of the production process.
The procurement method and the material sheets dimensions need to be adapted to enable the rubber pad flow to increasingly satisfy the customer demand. The customer demand comprises of first delivering products of the right quality, secondly on-time and thirdly to deliver against competitive costs.
The stable planning horizon of more than one year creates an opportunity for the rubber pad flow of the sheet metal department. It enables the flow to adapt the procurement method and sheet dimensions in accordance to future demand of production orders. Thereby increasing effectiveness of the production process while simultaneously reducing the incurred material costs.
Problem statement:
The production of sheet metal for low demand, high variety shows that the current performance in OTS, OTD, material efficiency and other types of waste can be improved. The batched release of orders in the milling process has been shown to negatively affect the production process. By altering the
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current state process it is possible to improve its performance. The main problem is to identify which process design changes can improve the performance of the purchase and order release process which in turn increase the effectiveness of the downstream production process.
1.4. Research objective and scope
The research scope of this master thesis is limited to the ‘pre’ production process of creating purchase orders, releasing POs and the milling process itself. This includes the way in which production orders are generated by the ERP system and the way in which purchase orders of sheet metal material are handled. The nesting of orders and the way in which orders are released to the production floor are of particular interest to this master research thesis. The production process that follows after the milling process steps is not considered in great detail because falls out of the scope of this research. No functional changes of the production process after the milling stage are considered as these would require a different research focal point.
The main research objective of this master thesis is to improve the sheet procurement method, the production order release and to adapt sheet dimensions according to product demand. Improving the ‘pre’ process of the production process to increase the effectiveness of the production process itself while at the same time producing against at least the same production costs. The effectiveness of the production process is measured by using two different KPI’s. First the OTP of the order release method is used to judge the effectiveness of the order release process. Variation incurred in the order release process disrupt the downstream production process and therefore need to be avoided as much as possible. The second KPI used to judge the effectiveness is the average number of POs that are release at once. Production orders are released in a batch because of the nesting and milling process. Form lean manufacturing it is known that is desirable to release orders in small increments to the production floor in order to increase the flow of production.8 The average number of production order that are
released at once is therefore indicative for the possibilities of releasing small increments of work.
1.5. Main research question and sub questions
Following the introduction of the current production system and the previously stated research objective, the main research question is formulated as follows:
How can the sheet procurement method, order release mechanism and sheet dimensions be improved to increase the effectiveness of the production process while simultaneously producing for least the same production costs?
This main research questions gives way to additional questions that need to be answered. These
sub-questions that need to be answered in support of the main research question are formulated as
follows:
1. What is lean manufacturing and how can these methods be applied to this process?
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2. How does the nester generate a custom milling pattern in the current process and how can this process be modeled within a simulation model?
3. What KPIs can be used to judge the effectiveness of the production process and the efficiency of the milling process?
4. How the purchase and order release process is currently handled and what are its main bottlenecks and constrains?
5. What is the financial performance of the current production process and what is the relative importance of material usage?
6. What is the effect of batched release of production orders on the performance of the production process?
7. What are possible alternative functional designs for the purchase and order release process?
1.6. Report structure
This report consists of 8 chapters and 14 appendices. Chapter 2 presents the research design and research methodology used in this research. Thereafter the current state production process is analyzed and it performance is uncovered in chapter 3. In chapter 4, the simulation model used to analyze the effects of analyze different future state process designs is explained in detail. The performance of the different future states are presented in chapter 5 based on key performance indications determined in chapter 2. Furthermore the relation between different variables is analyzed in this chapter. In chapter 6 conclusions are drawn based on the modelling results and the used theoretical framework. Finally in chapter 6 recommendation on process changes and future research are presented. There are 14 appendices included in the report that provide additional information. The first of these appendices is a scientific research paper of this master thesis.
2. Research Design
This chapter gives inside in the used research methodology for solving the main research question. First different used research methodologies for determine the characteristics of the production process are presented in paragraph 2.1. Thereafter in paragraph 2.2 the most important aspect of the lean manufacturing production philosophy which are used in this research are put forward. This production philosophy has been used to uncover the most important process constraints and in the development of alternative process solutions. Paragraph 2.3 presents a literature overview of the general packing and cutting stock problem. This problem is an integral part of the research objective and is therefore studied in greater detail. In paragraph 2.4 the reason for using a simulation model in order to answer the main research question are put forward. Finally a number of sub-questions are answered in section 2.5 in conclusion of this chapter.
2.1. Methodology
In order to comprehend the current order release and purchasing process at the sheet metal department a number of preliminary analyses are used in this research. The different used analysis techniques are clarified in more detail in this paragraph. First the two different types of functional analysis used are explained in more detail in section 2.1.1. Second the quantitative analysis is clarified
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in section 2.1.2. Last the statistical analysis on the current operational performance is elaborated in section 2.1.3.
2.1.1. Functional analysis
Mapping of a system is one of the most powerful tools in understanding and comprehending the constraints and operating procedures of any production system. There are many mapping tools that can be used to analyse the functional design of a process. In this master thesis two mapping tools have been used to visualize the current process. These two methods are applied side by side since they have different focal points. The combination of both tools therefore creates an even clearer picture of the current production process and its specific operating constraints and difficulties.
The first mapping tool that is used in the functional analysis of the process is Value Stream Mapping (VSM). The main focal point of the mapping tool is to visualize waste within a production system. In batch and queue operation much of the throughput time is actually waste (waiting time). Value stream mapping puts great emphasis on this waste and focusses on the reduction of throughput times. Value stream mapping is the visualisation tool used within lean manufacturing to create a clear overview of a system. Since this mapping tool is part of a larger management philosophy that is discussed in section 2.2, this mapping tool is not explained here. Value stream mapping is discussed in greater detail in section 2.2.5.
The second mapping tool used in this master thesis is the ‘PROPER’ model. This visualisation tool is able to provide useful and clear information on the different flows and transformation within a production system. This mapping tool is an integral part of the Delft System Approach (DSA) and is clarified in section 2.1.1.1.
2.1.1.1. Proper model and the Delft Systems Approach
The Delft Systems Approach is a multi-disciplinary communication and analysis tool that aim at closing the gap between theory and practice. The approach allows for streamlined communication between different specialist within a process or project. DSA is able to achieve this by creating a common language and by analyzing systems on a purely functional level. The main communication or mapping tool used within this method is the ‘PROPER’ model. (Veeke et al., 2008)
The ‘PROPER’ model is a mapping tool that visualizes the interactions within an organization on a functional level. The basic design of the ‘PROPER’ model is depicted in figure 10 below. In the model three different aspects of a system are explicitly visualized:
1. The product as a result of transformation. This flow is the ‘physical’ transformation from raw material on to a final product.
2. The flow of orders. In this flow orders are transformed into handled orders. This flow is the information flow that is required in the transformation of a product.
3. The resources (people and means) required to make a product. To make use of them, they must enter the system, and they will leave the system as used resources.
The control function in the model coordinates the transformations generating executable tasks derived from the orders and by assigning usable resources. Information flows both horizontally and vertically.
