The industrial company Scania CV AB is a world leader in the manufacturing of commercial vehicles. They offer a modular systems that include heavy trucks and buses that can be configured to a range of different needs. However, this adaptability leads to a problem where each order can have a large variance of assemblers that are re-quired during the manufacturing process. In other words, variant assemblers have a workflow that can shift from high workload to low workload and vice versa in a short period of time. To solve this problem a prototype will be developed. This prototype will be used to check if it’s possible to optimize the work schedule for variant assem-blers with the help of predictive simulations. The result of the study became an implementation in form of a prototype. This prototype is built up in two layers; a data layer and a simulation layer. The data layer provides the simulation layer with two different datasets. The first dataset is based on historical data and is derived from Scania’s production in Zwolle. The second dataset is based on synthetic data which is formed with a high utilization rate in order to mimic a better production situation with less product variants to assemble. The simulation layer consists of a DES-model that is modelled after a station in the final assembly of Zwolle. After a simulation has been executed, this layer generates a simulation result in form of a graph that presents the utilization rate for a group of variant assemblers. This will happened for each dataset in the data layer, in this case two times. The simulation result that got produced shows that it’s possible to create a simulation with predictive characteristics. A long term solution for Scania’s problem statement requires more research within the possibility of combining different technologies such as DES with predictive methods such as ML and GAs. / Industriföretaget Scania CV AB är världsledande inom tillverkning av kommersiella fordon. De tillhandahåller ett modulärt system som inkluderar tunga lastbilar och bussar som kan konfigureras till en rad olika behov. Den här anpassningsförmågan leder dock till ett problem där varje order som tillverkas kan ha en stor varians av hur många montörer som krävs under produktion. I andra ord så har variantmontö-rer ett arbetsflöde som kan skifta från hög arbetsbelastning till låg arbetsbelastning och vice versa under en kort period. För att lösa dessa typer av problem så ska en prototyp med prediktiva egenskaper så som Diskrete Event Simulering (DES). Denna prototyp ska undersöka om det är möjlighet att optimera arbetsscheman för variantmontörer med hjälpa av prediktiva simuleringar. Resultatet av studien blev en implementation i form av en prototyp. Denna prototyp är uppbyggd i två lager; ett datalager samt ett simuleringslager. Datalagret tillhandahåller simuleringslagret med två dataset. Det första datasetet är baserad på historisk data och är härledd från Scania’s produktion i Zwolle. Det andra datasetet är baserat på syntetisk data som är framtagen med en högre utnyttjandegrad för att efterlikna ett bättre produktionssitation med färre produkt varianter att montera. Simuleringslagret består av en DES-model som är modulerad efter en station i slutmontering i Zwolle. Efter att en simulering har exekverats så genererar detta lager ett simuleringsresultat i form av en graf som presenterar utnyttjandegraden för en grupp med variant montörer. Detta sker för varje dataset i datalagret, i detta fall två gånger. Simuleringsresultatet som togs fram visar att det är möjligt att ha skapa simuleringar med prediktiva egenskaper. En långsiktig lösning för Scania’s problem-beskrivningen kräver mer forskning inom möjligheten att kombinera tekniker som DES med prediktiva metoder som ML och GAs.

The automotive manufacturing facility is extremely complex and expensive system. Managing and understanding the dynamics of automotive manufacturing is a challenging endeavour. In the current era of dynamic global competition, a new concept such as Collaborative Lean Manufacturing Management (CLMM) can be implemented as an alternative for organisations to improve their Lean Manufacturing Management (LMM) processes. All members in the CLMM value chain must work together towards common objectives in order to make the LMM achievable in the collaborative environment. The novel research approach emphasises the use of Knowledge-Based (KB) approach in such activities as planning, designing, assessing and providing recommendations of CLMM implementation, through: a) developing the conceptual CLMM model; b) designing the KBCLMM System structure based on the conceptual model; and c) implementing Gauging Absences of Pre-requisites (GAP) analysis and Analytic Hierarchy Process (AHP) approach in the hybrid KBCLMM. The development of KBCLMM Model is the most detailed part in the research process and consists of five major components in two stages. Stage 1 (Planning stage) consists of Organisation Environment, Collaborative Business and Lean Manufacturing components. Stage 2 (Design stage) consists of Organisation CLMM Capability and Organisation CLMM Alignment components. Each of these components consists of sub-components and activities that represent particular issues in the CLMM development. From the conceptual model, all components were transformed into the KBCLMM System structure, which is embedded with the GAP and AHP techniques, and thus, key areas of potential improvement in the LMM are identified for each activity along with the identification of both qualitative and quantitative aspects for CLMM implementation. In order to address the real situation of CLMM operation, the research validation was conducted for an automotive manufacturer¿s Lean Manufacturing Chain in Malaysia. Published case studies were also used to test several modules for their validity and reliability. This research concludes that the developed KBCLMM System is an appropriate Decision Support System tool to provide the opportunity for academics and industrialists from the fields of industrial engineering, information technology, and operation management to plan, design and implement LMM for a collaborative environment. / Universiti Utara Malaysia and Ministry of Higher Education of Malaysia

The developed methodology for the modernization of the enterprise’s production system, based on a step-by-step method of managing production processes (6 sigma), the concept of lean manufacturing and statistical data analysis, can be used in projects to modernize the production systems of metallurgical enterprises, increasing their efficiency and competitiveness by: rational use of resources; increase labor productivity; staff involvement. The developed project for the modernization of the enterprise’s production system can be “replicated” at metallurgical enterprises, allowing them to reduce losses, rationally use resources and increase labor productivity. The concept of a project to modernize the enterprise’s production systems using lean manufacturing technologies and project management has found its practical application at the non-ferrous metallurgy enterprise KUZOTsM OJSC. / Разработанная методика модернизации производственной системы предприятия, основанная на пошаговом методе управления процессами производства (6 сигм), концепции бережливого производства и статистическом анализе данных, может быть использована в проектах по модернизации производственных систем металлургических предприятий, повышая эффективность их деятельности и конкурентоспособности за счет: рационального использования ресурсов; повышения производительности труда; вовлеченности персонала. Разработанный проект модернизации производственной системы предприятия может «тиражироваться» на металлургических предприятиях, позволяя сокращать потери, рационально использовать ресурсы и повышать производительность труда. Концепция проекта модернизации производственных систем предприятия с использованием технологий бережливого производства и проектного управления нашло свое практическое применение на предприятии цветной металлургии ОАО «КУЗОЦМ».

This study has been conducted at Scania Engine Assembly, in particular in an production area that produces Marine Engines. Scania always strives for continuous improvement and the purpose of this study has been to create an overview of the production area Marine-completion, where the marine components are assembled. The goals were to create a current state analysis, propose a future state analysis and propose suggestions of solutions for improvement of Marine-completion. The research question was: How can the strategies for the current state analysis be chosen, used and analyzed in order to accomplish a successful current state analysis?. The research methodology in this study was conducted using qualitative and quantitative research strategies, where both primary and secondary data were collected. The theoretical framework was divided into four subsections: Production systems, project management, technical solutions of today and supporting literature for solutions. The main method of this study was collecting data. The data included layout of the production, assembly times, quality deviations, engine variant classifications, Value Stream Mapping, Safety, Health and Environment related deviations and costs. Based on the current state, a future state was developed. The results of the current state analysis was that there are a total of 20 main variants of marine engines which have different assembly times. The assembly time can vary from approximately 45 minutes to 3 hours and 35 minutes for straight engines and approximately 4 hours to 8 hours for V8 engines. The mean results from Value Stream Mapping concluded a distribution of 40 percentage Value Adding and 60 percentage Non-Value Adding, where the largest waste from Non-Value Adding activities was bringing parts. Most of the quality deviations were caused by the method, where the biggest problem was regarding "tool insufficiency". Safety, Health and Environment related deviations were identified, where the largest problems were "risk". The future state analysis ended up in three cases, which explains the possible savings and future states. The Failure Mode and Effects Analysis resulted in 7 failure modes, where "Engine-card missing tasks/parts" had the largest rating. The suggestion of solutions resulted in a new layout, new routines with the engine-cards with digital screens and some other smaller suggestions. This study concluded in three main suggestions of solutions about "Newlayout at Marine-completion ", "Digital screens at each station" and "Continuous update of enginecards", which resulted in three assignment directives that Scania can further work with in the future. / Detta arbete har utförts på ett produktionsområde i Scanias motormontering i Södertälje, Stockholm. Scania strävar alltid mot ständiga förbättringar och detta arbete uppfyller det genom syftet att skapa en kartläggning över produktionsområdet med fokus i förbättringar. Målen med detta arbete var att kartlägga nuläget i Marinkompletteringen samt skapa ett framtidsläge tillsammans med föreslagna förbättringsförslag. Den forskningsrelaterade frågeställningen för detta arbete var: Hur kan strategierna för nulägesanalysen väljas, användas och analyseras för att uppnå en lyckad nulägesanalys? Metoden för litteraturstudien som utförts för detta arbete använde kvalititativa och kvantitiva forskningsmetoder där både primär och sekundärdata samlades. Det teoretiska ramverket var uppdelat i fyra delkapitel: Produktionssystem, projektledning, tekniska lösningar idag och stödjande litteratur för lösningar. Huvudmetoden för detta arbete var datainsamlingen som inkluderade aspekter som layout på området, monteringstider, kvalitetsavvikelser, motorvarianternas klassificering, värdeflödesanalys, avvikelser kopplat till säkerhet, hälsa, miljö och kostnader. Utifrån nulägesanalysen utvecklades framtidsläget fram. Resultaten från nulägesanalysen påvisade en total mängd av 20 olika huvudvarianter på marinmotorerna som monteras i marinkompletteringen med olika monteringstider. Monteringstiderna kunde sträcka sig mellan 45 minuter till tre timmar och 35 minuter för raka motorer och ungefär fyra till åtta timmar när det gäller V8 motorer. Medelvärdet på resultatet av värdeflödesanalysen resulterade i en fördelning av 40 procent värdeskapande tid och 60 procent icke-värdeskapande tid där det största slöseriet tillkom vid upphämtning av artikel. De flesta kvalitetsbristerna orsakades av metodiska fel där det mest förekommande metodiska felet var framkomlighet för verktyg. Bristerna kring säkerhet, hälsa och miljö identifierades och den mest förekommande bristen var gällande risker på arbetsplatsen. Analysen av framtidsläget resulterade i tre scenarion som vardera förklarar möjliga kostnadsbesparingar vid utfasning av olika icke-värdeskapande aktiviteter. Failure Mode and Effects Analysis som utfördes resulterade i sju feltyper varav "brist på information i motorkort" hade högst risktal. Rekommenderade åtgärder för Failure Mode and Effects Analysis resulterade i förslag om ny layout, nya rutiner gällande motorkort med digitala lösningar samt ett flertal mindre lösningar. De föreslagna lösningar som gavs till Scania i detta arbete var tre konkreta huvudförslag angående "ny layout på marinkompletteringen", "digitala skärmar på vardera station" och "kontinuerlig uppdatering av motorkort" vilket i sin tur resulterade i tre uppdragsdirektiv som Scania fortsatt kan jobba med i framtiden.

The research aims to investigate the lack of cohesive workflow of production lines within a company, exploring the factors and dynamics at play. It also seeks to analyze the identified issues, focusing on their root causes and potential impacts on operational efficiency. An important aspect of the research is the consideration of value stream mapping (VSM). The methodology is based on a literature review and a single-case study. The literature review, including a systematic review, was conducted to identify existing practices. To explore the research objectives, a case study was performed, examining the industrial implementation and challenges of using the VSM tool. The current state VSM was designed and analyzed, identifying various types of waste within the workflow. Based on this analysis, a future state VSM was recommended to address the inefficiencies. The field of study is well-researched but has a notable gap regarding the application of VSM in complex industrial settings. The research identified inadequacies for using and implementing VSM in organizations, aiming to fill this gap. The research concluded that while there are several benefits to using VSM, there are also challenges that need to be addressed. To bridge these challenges and support decision-making in the improvement process, the study proposes specific recommendations. The study faced limitations, particularly in data collection due to time constraints and validity concerns. The data collection period was limited to less than two months. Additionally, the complexity of the data led to generalizations in the creation of the VSM. This "good enough" approach, however, is not deemed to significantly affect the study's overall validity or reliability. By providing a systematic way of mapping, the research enhances operational efficiency by more efficient use of resources, reduced cycle times, improving process flow, and facilitating better decision-making. These efforts lead to improved overall performance within the company.

This dissertation reports the investigation and combination of optimization methodologies and the result of implementing them within a production environment. A literature survey was conducted on the optimization methodologies Lean Manufacturing and theory of constraints (TOC). A number of production optimization methodologies were studied and considered for application to the case study organisation. Due to the small size and relative simplicity of the operation, these methodologies had to be simplified and combined into a more relevant form. A refractory manufacturer was used as a case study for the investigation into the optimization of the dry batch plant. Lean Manufacturing and TOC are optimization methodologies that could be employed to optimize the dry batch plant. Tools from these methodologies were used to investigate problems identified within the production process that were causing the batching plant to perform non-optimally. A time and motion study was conducted and a process flow chart was created to understand the production process. Wasteful activities were identified using a value stream map and a flow process chart was used to visualise the movement within the production process. A 5-Why analysis was conducted to determine the root causes. An optimization plan was created to eliminate the wasteful activities and the operational measures, that is throughput, inventory and operating expense, were used as to determine what the effect the optimization plan would have on the wasteful activities (Lean Manufacturing) found within the batching plant and the organisation. The results of the combined effect of the optimization plan are discussed focusing on the improvements in the operational measures and the increase in profit from sales. Future research is suggested to improve the benchmarking of the optimization plan and any future improvements that the organisation might implement. / MSc (Development and Management Engineering), North-West University, Potchefstroom Campus, 2015

This dissertation reports the investigation and combination of optimization methodologies and the result of implementing them within a production environment. A literature survey was conducted on the optimization methodologies Lean Manufacturing and theory of constraints (TOC). A number of production optimization methodologies were studied and considered for application to the case study organisation. Due to the small size and relative simplicity of the operation, these methodologies had to be simplified and combined into a more relevant form. A refractory manufacturer was used as a case study for the investigation into the optimization of the dry batch plant. Lean Manufacturing and TOC are optimization methodologies that could be employed to optimize the dry batch plant. Tools from these methodologies were used to investigate problems identified within the production process that were causing the batching plant to perform non-optimally. A time and motion study was conducted and a process flow chart was created to understand the production process. Wasteful activities were identified using a value stream map and a flow process chart was used to visualise the movement within the production process. A 5-Why analysis was conducted to determine the root causes. An optimization plan was created to eliminate the wasteful activities and the operational measures, that is throughput, inventory and operating expense, were used as to determine what the effect the optimization plan would have on the wasteful activities (Lean Manufacturing) found within the batching plant and the organisation. The results of the combined effect of the optimization plan are discussed focusing on the improvements in the operational measures and the increase in profit from sales. Future research is suggested to improve the benchmarking of the optimization plan and any future improvements that the organisation might implement. / MSc (Development and Management Engineering), North-West University, Potchefstroom Campus, 2015

Additive manufacturing is an industrial process, developed in the early 1980s and currently used in several industries such as the medical, aircraft and automotive industries. In the first place,additive manufacturing was mostly usedby manufacturing industries to produce prototypes, models and patterns. Nowadays, this technology can be used at any point in the lifecycle of a product from pre-production(rapid prototyping and rapid tooling) to production (direct manufacturing). This technology is especially adapted for the production of limited series of small and geometrically complex components.The purpose of this study is to identify howadditive manufacturing affects operational performance during the development and production phases, specifically in the case of the automotive industry.With this purpose in mind, I have collected primary and secondary data through a qualitative study using both in-depth semi-structured interviewsand archival records found on automotive companies’ websites. The objective of collecting multiple sources datawas to gain a reliable and comprehensive perception of the situation and understand the effects of additive manufacturing on operational performance, and more precisely on the seven production wastesdefined on lean practices, to be able to answer my research question. The data are analyzed using an inductive thematic analysis approach and testthe presupposition that emerged from the empirical findings. Through the analysis of the data collected, I came to the conclusion that additive manufacturing is mostly used during the prototyping phase and sometimes also used for rapid tooling. But it appears that this technology is only used for direct manufacturing in some specific niche markets such as luxury carmakers. Another interesting finding concerns the use of additive manufacturing for marketing purpose. Concerning operational performance, the impacts of additivemanufacturing remainlimited, and contrary to what some authors said, the use of this technology is still marginal in the automotive industry compared to traditional manufacturing.

Thesis (MBA (Business Management))--University of Stellenbosch, 2009. / ENGLISH ABSTRACT: In the face of global competition manufacturers are increasingly finding themselves having to redefine the way they do business. Despite this, and while lean manufacturing has been widely adopted as an inherently superior form of manufacturing when compared to mass production, many companies continue to operate according to a traditional mass production philosophy. This research aims to validate and quantify the existence of a correlation between the presence of lean manufacturing and improved performance in important financial indicators with a view to encouraging the more rapid adoption of lean manufacturing. The intended outcome of this research is therefore firstly an analysis that either confirms or refutes the existence of a correlation between selected lean manufacturing practices and selected financial indicators, and secondly a quantification of the strength of the identified relationship, if any. There are four sub-problems that were identified as being central to the research aims. The first relates to the identification of foundational principles associated with lean manufacturing, while the second relates to the identification of manufacturing practices associated with each principle that can be observed and tested for. The third entailed the evaluation of existing literature on links between lean manufacturing and financial performance. The fourth entailed the development of a set of hypotheses and methodology for the testing of relationships between lean manufacturing practices and financial indicators. The four principles, and their associated practices, were as follows: • Just In Time: kanban; • Total Quality Management: andon and poka-yoke; • Continuous improvement: standardisation of work practices, green areas and suggestion schemes; and • Team-based work organisation: teams, single-piece flow between team members and team leader roles. The review of existing literature provided some guidance in respect of financial performance measures that should be included in the study, but fell short of confirming the type of relationships and correlations sought for the purpose of this research. Data on the financial performance of 22 automotive component manufacturers were obtained from the Benchmarking and Manufacturing Analysts SA (Pty) Ltd’s benchmarking database while data on lean manufacturing practices were obtained through structured observations at the 22 companies between January 2008 and December 2008. Through evaluating Spearman rank correlation coefficients conclusive findings were obtained in respect of the existence of a relationship and a positive correlation between each of the following pairs of variables: • Kanban and average growth in sales; • Kanban and change in Return on Investment; • Andon and operating profit as a percentage of sales; • Poka-yoke and operating profit as a percentage of sales; • Poka-yoke and growth in sales; • Green areas and operating profit as a percentage of sales; and • Standardisation of work practices and operating profit as a percentage of sales. During the analysis and interpretation of the findings value chains dynamics, operational measures, and control variables were cited as key considerations for further research in this field. The paper concludes by suggesting that a study of this nature replicated in the automotive industry in a different economy would likely result in similar outcomes, but that the same outcomes may not necessarily be obtained if the study was replicated in a different industry in the same economy. / AFRIKAANSE OPSOMMING: Met die uitdagings van globale mededinging en vrye toegang tot wêreld markte is vervaardigers blootgestel aan die behoefte om hulle besigheidsprosesse voortdurend te vernuwe en te optimiseer. Ten spyte van die feit dat “Lean Manufacturing” spesifiek in die vervaardigings industrie aanvaar is as die voorkeur model bo die meer tradisionele massa produksie model sukkel maatskapye steeds met die implimentering daarvan. Die doel van hierdie navorsing is om te toon dat daar ‘n verwantskap bestaan tussen die beginsels van “Lean Manufacturing” en die winsgewindheid van maatskappye. Meer spesifiek word daar gesoek na sleutel finansiële aanwysers in die besigheid, en hulle verwantskap met geselekteerde “Lean Manufacturing” beginsels. Daar word gepoog om die verwantskappe te kwantifiseer, en hierdie resultate dan te gebruik as basis vir die motivering om hierdie beginsels verder en vinniger in die vervaardigings industrie te implimenteer. Vier subprobleme is geidentifiseer om die voorgestelde navorsing logies te benader. Die eerste hou verband met die identifisering van die kern beginsels van “Lean Manufacturing”, en die tweede met die identifisering van vervaardigings praktyke wat assosieer kan word met elkeen van die beginsels. Die derde subprobleem is die analise en vewerking van bestaande literatuur met die doel om die verwantskap tussen die identifiseerde kern beginsels van “Lean Manufacturing” en finansiële indikatore te evalueer. Laastens word ‘n hipotese ontwikkel om die identifiseerde verwantskappe te toets en te evalueer. Die vier beginsels en die assosieërde praktyke is: • “Just In Time”: kanban; • Algemene Kwaliteits Bestuur: andon en poka-yoke; • Voortdurende Verbetering: standardisering van werksprosesse; en • Spangebaseerde Organisasies: Spanwerk. Die bestudering van bestaande literatuur het ‘n riglyn geskep vir van die finansiële indikatore wat in ag geneem moet word in die studie. Dit het wel geblyk dat die tipe verwantskap nie duidelik definieer is nie. Die finansiële data van 22 motor komponent vervaardigers is verkry van Benchmarking and Manufacturing Analysts SA (Pty) Ltd’s se databasis. Die data oor “Lean Manufacturing” is verkry deur gestruktureerde waarnemings en onderhoude by dieselfde 22 maatskapye oor die tydperk Januarie 2008 tot Desember 2008. Deur die evaluering van “Spearman rank” korrelasie koëfisiënte kon ‘n korrelasie tussen die volgende veanderlikes verkry word: • Kanban en die gemiddelde groei in verkope; • Kanban en die verandering in die opbrengs op belegging; • Andon en die operasionele wins as ‘n persentasie van verkope; • Poka-yoke en die operasionele wins as ‘n persentasie van verkope; • Poka-yoke en die groei in verkope; • Groen areas en die operasionele wins as ‘n persentasie van verkope; en • Standardisering van werksprosedures en die operasionele wins as ‘n persentasie van verkope. Na aanleiding van die analise en interpretasie van die bevindinge opgelewer deur die studie word die verdere bestudering van die veld sterk aanbeveel. Waardeketting dinamika, operasionele maatstawwe, en beheer veranderlikes is identifiseer as kernaspekte van so ‘n verdere ondersoek. Dit moet egter benadruk word dat die herhaalbaarheid van die studie moontlik sal wees in ander ekonomiese toestande, maar nie noodwendig dieselfde resultate sal lewer vir ander industrieë nie.

The automotive manufacturing facility is extremely complex and expensive system. Managing and understanding the dynamics of automotive manufacturing is a challenging endeavour. In the current era of dynamic global competition, a new concept such as Collaborative Lean Manufacturing Management (CLMM) can be implemented as an alternative for organisations to improve their Lean Manufacturing Management (LMM) processes. All members in the CLMM value chain must work together towards common objectives in order to make the LMM achievable in the collaborative environment. The novel research approach emphasises the use of Knowledge-Based (KB) approach in such activities as planning, designing, assessing and providing recommendations of CLMM implementation, through: a) developing the conceptual CLMM model; b) designing the KBCLMM System structure based on the conceptual model; and c) implementing Gauging Absences of Pre-requisites (GAP) analysis and Analytic Hierarchy Process (AHP) approach in the hybrid KBCLMM. The development of KBCLMM Model is the most detailed part in the research process and consists of five major components in two stages. Stage 1 (Planning stage) consists of Organisation Environment, Collaborative Business and Lean Manufacturing components. Stage 2 (Design stage) consists of Organisation CLMM Capability and Organisation CLMM Alignment components. Each of these components consists of sub-components and activities that represent particular issues in the CLMM development. From the conceptual model, all components were transformed into the KBCLMM System structure, which is embedded with the GAP and AHP techniques, and thus, key areas of potential improvement in the LMM are identified for each activity along with the identification of both qualitative and quantitative aspects for CLMM implementation. In order to address the real situation of CLMM operation, the research validation was conducted for an automotive manufacturer's Lean Manufacturing Chain in Malaysia. Published case studies were also used to test several modules for their validity and reliability. This research concludes that the developed KBCLMM System is an appropriate Decision Support System tool to provide the opportunity for academics and industrialists from the fields of industrial engineering, information technology, and operation management to plan, design and implement LMM for a collaborative environment.