This master thesis describes and proves how companies can improve their operational performance and supplier relationships by using modern collaborative and planning practices, specifically the Collaborative Planning Forecasting and Replenishment (CPFR) concept. The theoretical part depicts main developments in supply chain planning over time, shows common challenges in the world of supply chain and offers possible solutions in terms of collaborative supply chain planning practices. The practical part analyzes the CPFR process between one of the leading providers of telecommunications services T-Mobile and its major mobile handset supplier Nokia. The concluding part defines gaps between an ideal to-be process of supply chain collaboration and the status quo process. Status quo benefits of current CPFR processes are described as well.

This thesis addresses industrial energy issues from a production economic perspective. During the past decade, the energy issue has become more important, partly due to rising energy prices in general, but also from a political pressure on environmental awareness concerning the problems with climate change. As a large user of energy the industry sector is most likely responsible for a lot of these problems. Things need to change and are most likely to do so considering current and assumed future governmental regulations. Thus, the energy intensive process industries studied and focused on in this thesis exemplify the importance of introducing a strategic perspective on energy, an appropriate approach for planning, as well as the possibilities of including energy issues in a production and supply chain planning model. The thesis aims to provide models, methods and decision support tools for energy related production and supply chain planning issues of relevance for process industries as well as for other energy intensive industries. The overall objectives are to analyze the strategic importance of energy management, production and supply chain planning, and the opportunities provided when energy is included in a production and supply chain planning model. Three different studies are carried out, analyzed, and presented as in this thesis. The first study is a case study at a specialty chemicals company and resulted in the first paper. Since the energy issue is not only a cost issue driven by supply and demand, but also a political issue due to its environmental aspects, it is likely to believe that political influence and especially continuity will have escalating effect on the energy intensive process industry sector. Thus, the strategic dimension of energy is highly relevant in this thesis. The importance of organizational integration, having a main responsible person, locating core business, and political continuity are addressed as prerequisites for including energy into the corporate strategy. Regarding long term profitability, the importance of correctly utilizing the energy system by appropriate energy planning and with respect to energy efficiency and effectiveness in both flexibility and investment issues are addressed. Further on, the quest of finding alternative revenue while striving for a proper exergy usage is addressed. The second study is a multiple case study with four different case companies involved; pulp, specialty chemicals, specialty oils, as well as a pulp and paper company. The need for improved production and supply chain planning is also addressed where for instance the lack of planning support for process industries is still an area of improvement. The production and supply chain planning in process industries is found to be rather poor compared to regular manufacturing companies. The planning methods found are often tailor made and adapted to the individual characteristics that are typical for many process industries. It has further on been difficult to distinguish similarities and differences among process industries regarding these planning issues and thus hard to generalize. The third study focuses on mathematical modelling and programming developing a combined supply chain and energy optimization model for a pulp company. Taking the first papers together there are reasons to believe that a planning and optimization model that take energy aspects in consideration, as a previously missing link, will contribute to improve the operations in process industries. A clear impact of involving energy issues into the supply chain planning is shown. The results show that a different production schedule is optimal when the energy issues are applied, and depend on, for instance, variations in energy prices such as the one for electricity. This is shown by using a model for a supply chain where the energy flow, and especially the utilization of by-products, also is involved.

In today’s competitive market it is more important than ever to have effective and efficient Supply Chain Planning. Despite its wide adoption and many years of development, Sales and Operational Planning, one of the most commonly applied tactical Supply Chain Planning processes, is not generating the desired results as companies are still experiencing difficulties in synchronizing demand and supply. Furthermore, a company’s competitiveness depends on its knowledge management and how that knowledge is disseminated across functions. Therefore, a case study was conducted with the purpose to investigate how knowledge management is used in the Sales and Operational Planning process to streamline its operations. The study presents a conceptual framework built on prior research on how to use knowledge management in the Sales and Operational Planning process. The framework highlights the importance of alignment of targets and information as well as continuous documentation and learning to improve the streamlining of the process. Additionally, the study illustrates linkages between the stages of creating, spreading, and applying knowledge by applying the framework to the case company. The study identified a gap in research where the combination of Sales and Operational Planning and Knowledge Management had not fully been explored. This gap was addressed by the creation of the conceptual framework. The practical contribution identified both systematic, functional, and individual areas of Knowledge Management that can work to streamline the process. / Dagens konkurrenskraftiga marknad gör att det är viktigare än någonsin att ha en effektiv planering av försäljningskedjan. Sälj- och verksamhetsplanering är en av de mest tillämpade taktiska processerna för planering av försäljningskedjan. Trots sin breda användning och många år av utveckling så genererar inte processen de önskade resultaten då företag fortfarande upplever svårigheter i att synkronisera utbud och efterfrågan. Fortsättningsvis finns det korrelation mellan ett företags konkurrenskraft och kunskapsspridning samt hur kunskap sprids internt mellan funktioner. Därför genomfördes en fallstudie med syftet att undersöka hur kunskapshantering kan integreras i sälj- och verksamhetsplaneringen för att effektivisera processen. Studien presenterar ett ramverk baserat på tidigare forskning, om hur sälj- och verksamhetsplaneringen kan effektiviseras genom kunskapshantering. Ramverket belyser vikten av samspel mellan mål och information samt kontinuerlig dokumentation för effektivisering av processen. Vidare illustrerar studien kopplingar mellan stadierna att skapa, sprida och använda kunskap genom att tillämpa ramverket på det undersökta företaget. Studien identifierar ett forskningsgap där kombinationen av sälj- och verksamhetsplanering och kunskapshantering inte har undersökts fullständigt. Detta forskningsgap adresseras genom skapandet av ramverket. Det praktiska bidraget består av både systematiska, funktions-baserade och individ-baserade områden inom kunskapshantering som kan arbeta för att effektivisera processen.

Submitted by William Justo Figueiro (williamjf) on 2015-07-03T13:21:02Z No. of bitstreams: 1 31.pdf: 1544600 bytes, checksum: b5f309e37324900dbc54bfa8402417d6 (MD5) / Made available in DSpace on 2015-07-03T13:21:02Z (GMT). No. of bitstreams: 1 31.pdf: 1544600 bytes, checksum: b5f309e37324900dbc54bfa8402417d6 (MD5) Previous issue date: 2011-08-26 / Nenhuma / Este estudo examina como a estratégia de manufatura e o planejamento da cadeia de suprimentos influenciam na antecipação de novas tecnologias e o efeito dessas no desempenho operacional. Foi considerado que a antecipação de tecnologia de manufatura pode ser uma fonte de diferencial competitivo, baseado nas proposições de Hayes e Wheelwrigth (1984). Os autores estabeleceram que a manufatura pode desenvolver pelo menos quatro papéis ou estágios na estratégia competitiva da empresa, e que no quarto e último estágio a empresa busca se antecipar a novas tecnologias de manufatura para os produtos que virão a ser produzidos. Para isso, é proposto um modelo teórico que liga a estratégia de manufatura à cadeia de suprimentos, incorporando nessa relação os conceitos de Parcerias com Fornecedores e de Integração Funcional. Para construir esse modelo, foram usados os construtos do projeto de pesquisa internacional chamado High Performance Manufacturing (HPM). A técnica de coleta de dados foi desenvolvida através de uma survey, e os dados foram analisados estatisticamente por meio de Modelagem de Equações Estruturais. Conforme indicado na literatura, a análise dos dados comprovou a relação positiva e significante entre a Estratégia de Manufatura e a Antecipação de Novas Tecnologias (ANT), sendo a Estratégia de Manufatura a variável de maior poder de explicação da variação da variável ANT entre todas as variáveis consideradas. Da mesma forma, as decisões de tecnologias relacionadas com custo e com os demais critérios diferenciadores não possuem o mesmo nível de influência de seus antecedentes. A relação entre o Planejamento da Cadeia de Suprimentos e a ANT também se confirmou como positiva, mas com menor poder de explicação para a variação da ANT. Os resultados mostraram a fraca influência direta da estratégia de manufatura e do planejamento da cadeia de suprimentos sobre o desempenho, sendo o planejamento da cadeia de suprimentos não significante na relação com o custo. Finalmente, o estudo traz uma contribuição para as discussões teóricas e práticas ao demonstrar que, para o direcionamento da ANT via estratégia de manufatura, as empresas podem avaliar qual impacto as tecnologias buscadas terão em relação às diferentes prioridades competitivas, aparecendo potencialmente os conceitos de trade-off. Esses resultados mostram a importância do estudo da ANT para a competitividade da empresa devido a sua influência no desempenho operacional e a importância clara da Estratégia de Manufatura nesse alinhamento para a competição da empresa, conforme indicado por Hayes e Wheelwright (1984). / This research paper examines how manufacturing strategy and supply chain planning (SCP) influence the anticipation of new technologies (ANT) and their effects on operational performance. We consider that manufacturing technology anticipation could be a source of competitive advantage based on the propositions of Hayes and Wheelwrigth (1984). The authors established that manufacturing can play at least four major roles in a firm’s competitive advantage, and in the last stage efforts are made to anticipate new manufacturing technologies for its future products. A theoretical model is proposed that links manufacturing strategy to supply chain planning. The model incorporates supplier partnership and function integration concepts in the relationship between manufacturing strategy and supply chain planning. In order to build the model, we used the constructs from the international research project High Performance Manufacturing (HPM). The data collection uses a survey methodology, and the data were analyzed with Structural Equation Modeling. As indicated in the literature, the data analysis show the positive and significant relationship between manufacturing strategy and ANT, with the manufacturing strategy the construct with the highest effect on the ANT among all the constructs considered. The findings indicate that the technological decisions related with cost and the rest of the competitive priorities do not share the same level of effect of their antecedents. The relationship between supply chain planning and ANT was found positive, but with less effect on ANT. The results show the weak direct effect from manufacturing strategy and SCP on performance, with SCP having a non significant effect on cost. Finally, the research contributes to operational management theory and practice showing that ANT are directed through manufacturing strategy and the firm’s could evaluate which impact the technologies will have on the competitive priorities, potentially bringing the trade-off concept. These findings demonstrate the importance of the ANT study for the competitive of the firm, especially because of its influence on operational performance and the clear importance of manufacturing strategy on this alignment, as stated by Hayes and Wheelwright (1984).

本文提出一供應鏈規劃(Supply Chain Planning, SCP)整合的簡明模型，該模型能夠協助晶圓代工公司達到供應鏈規劃整合的目的。模型內含兩個主要部份。一是三維供應鏈規劃網路暨資訊傳遞模型((簡稱三維立體模型)，另一個是適用於晶圓代工業的核心供應鏈規劃模型(簡稱規劃引擎)。 三維立體模型，它整合供應鏈內垂直與水平方向的參與者，同時也將時間軸上不同時程規劃(長、中、短期)一起併入模式考量範圍。根據公司參與的製造步驟，三維立體模型亦可彈性地由基本型擴充為擴張型。不論是基本型或是擴張型，各節點根據座標軸(coordinate)定義功能並提供服務，這種設計可以提高模式穩健度，減低因外界的變化而引發系統變更需求。系統也可以由座標幫助輕易找到可以提供服務的節點與資訊傳遞的控制(資訊傳遞規則)，資訊可以有序的傳遞分享。 在核心規劃引擎部份，針對晶圓代工產業在長、中、短期規劃需求，以及產業長生產前置時間時間的特性，設計隨時間變化參數適用於長、中期的線性規劃 (Linear Programming, LP) 模型與適用於短期規劃的啟發式 (heursitic ) 演算模型，配合三維立體模型所定義結構與資料傳遞規則，各時程(長、中、短期)製造階段節點皆可獲取必要資料並進一步以適當規劃法則求取同步與整合的規劃結果。 最後利用物件導向分析 (object-oriented analysis) 中順序圖 (sequence diagram)、狀態圖(state diagram)、與類別圖 (class diagram) 展示三維立體模型的系統應用架構(application framework)。 關鍵字：供應鏈規劃，規劃整合，資訊傳遞，線性規劃，物件導向分析，應用架構

Purpose: The purpose of this study is to identify and develop relevant keyperformance indicators within the warehouse operations in amanufacturing company, and how they can be used for control. Research question: In a manufacturing company, which are the most important KPIs forcontrolling and monitoring the warehouse operations, and how can thoseKPIs be developed?Methodology: This master thesis is based on a case study at a pharmaceutical companynamed Fresenius Kabi. A qualitative approach has been used whereprimary data was collected through 10 structured & semi structuredinterviews and through observations in the warehouses to understand thecurrent state. Secondary data was used in form of academic papers to seewhat previous research had to say about KPIs and operation & processmanagement. Internal documents were also used as a secondary source. Findings: Two key performance indicators have been developed, productivity andcost efficiency. A template has been designed to produce the KPIs. Thisstudy contributes to the understanding of how to develop KPIs that fits amanufacturing company´s warehouse operations and a recommendation onhow you could develop a system for producing the data.

No description available.

This thesis deals with the problems of design and operation of process supply chains. Process supply chains face many challenges due to volatile market conditions, production and transportation delays, and stiff market competition, which ultimately affect their profitability. Supply chain management (SCM) is the process of managing the flow of materials and information within supply chain to optimize the SC performance. SCM is carried out using a hierarchical decision-making framework, where the top most layer looks at network design and the bottom-most layer deals with scheduling day-to-day activities. In this research, the systems engineering principles are applied to devise an improved methodology for supply chain optimization (SCO). First, we consider the design of supply chain in the presence of demand uncertainty. The representation of network topology plays an important role in deriving the optimal network design. In real practice, the shipping cost for transferring goods from one location to another is determined based on service time and quantity. More importantly, the cost associated with establishing a transportation linkage is relatively small for existing transportation infrastructure and can be changed if beneficial. The flexibility of changing the transportation routes is included in the network topology representation by the explicit inclusion of time limited transportation contract agreements. Further, the customer demand is volatile, and it is very difficult to predict accurately. To handle the demand uncertainty, a two-stage stochastic programming formulation is applied in the SC design approach. Next, we consider the problem of handling uncertainty in SC planning by applying a system engineering control principle, robust model predictive control (MPC). The uncertainty in model parameters (yield) and demand are captured by stochastic programming. In this approach, the planning activities are represented by a hybrid model with decisions governed by logical conditions/rulesets. An MPC based rolling horizon control framework is used to schedule the planning activities, where the SC performance is expressed using a multi-criterion objective comprising customer service and economics. The uncertainty in demand and yield are propagated by two mechanisms - an open-loop approach, and an approximate closed-loop strategy. Finally, we consider the problem of integration of SC planning and scheduling. Due to the use of different time scale models for planning and scheduling, the decision derived from the planning layer may result in infeasibility when those targets are implemented at the scheduling level, which ultimately affects the supply chain efficiency. To address this issue, we model tactical and operational planning activities using an integrated hybrid time modeling approach in which the first few planning periods are formulated using an operational planning model and the remaining time periods are modeled with a tactical planning model. The main rationale for formulating an integrated model is that customer demand forecast becomes less accurate for a future time, therefore making a detailed planning model unnecessary. A key benefit of using a hybrid modeling approach is that it avoids the problem of infeasibility encountered in the hierarchical decision framework, as well as the computational burden associated with the use of a detailed planning model over a long time horizon. We employ an MPC based rolling horizon framework as a tactical decision policy where the integrated model is used to predict the system behavior. / Thesis / Doctor of Philosophy (PhD)

Tesis por compendio / [ES] La innovación en los métodos de trabajo con nuevos sistemas de producción ajustados, sostenibles y resilientes, así como la gestión tecnológica eficaz son las tendencias actuales para mejorar el rendimiento en las organizaciones. Así, esta tesis doctoral investiga las contribuciones teóricas y formula un modelo conceptual con el uso de herramientas de fabricación ajustada o lean manufacturing (LM) y de la industria 4.0 (I4.0) para procesos de planificación de la producción en las cadenas de suministro. Además, se utiliza la optimización como tecnología facilitadora de la I4.0 para desarrollar la propuesta de solución. La metodología que se utiliza es bibliográfica, exploratoria y experimental; se aplican técnicas de investigación operativa, normalización de datos y casos de estudio en empresas industriales. Como punto de partida se revisa la literatura existente relacionada con la LM y las tecnologías de la I4.0 en el contexto de la cadena de suministro. Seguidamente, se diseña un modelo conceptual denominado LSCP 4.0 para facilitar la toma de decisiones en los niveles de decisión estratégico, táctico y operativo. Se trata de una relación estructurada entre los paradigmas lean, ágil, sostenible, resiliente y flexible para mejorar el rendimiento de las cadenas de suministro mediante la aplicación de las tecnologías facilitadoras de I4.0. Basado en esto, se propone un modelo matemático de optimización lineal entera-mixta, denominado LSCP 4.0, para maximizar los beneficios y planificar simultáneamente la producción, inventario de materiales y productos terminados satisfaciendo la demanda proveniente de previsiones y pedidos en firme en una cadena de suministro de cinco niveles. Novedosamente, se combinan enfoques de producción de just in time (JIT) y planificación de requerimientos de materiales (MRP). Ambos modelos para LSCP 4.0, i.e., conceptual y matemático, se validan en casos de estudio reales de la industria de calzado. Adicionalmente, se considera el uso de otra tecnología facilitadora de la I4.0 como la computación en nube para abordar el problema del intercambio de información entre los nodos de la cadena de suministro. Así, se propone un modelo de datos normalizado para la fabricación colaborativa en la nube aplicado a la industria del calzado. / [CA] La innovació en els mètodes de treball amb nous sistemes de producció ajustats, sostenibles i resilients, així com la gestió tecnològica eficaç són les tendències actuals per a millorar el rendiment en les organitzacions. Així, aquesta tesi doctoral investiga les contribucions teòriques i formula un model conceptual amb l'ús d'eines de fabricació ajustada o lean manufacturing (LM) i de la indústria 4.0 (I4.0) per a processos de planificació de la producció en les cadenes de subministrament. A més, s'utilitza l'optimització com a tecnologia facilitadora de la I4.0 per a desenvolupar la proposta de solució. La metodologia que s'utilitza és bibliogràfica, exploratòria i experimental; s'apliquen tècniques d'investigació operativa, normalització de dades i casos d'estudi en empreses industrials. Com a punt de partida es revisa la literatura existent relacionada amb laLM i les tecnologies de la I4.0 en el context de la cadena de subministrament. Seguidament, es dissenya un model conceptual denominat LSCP 4.0 per a facilitar la presa de decisions en els nivells de decisió estratègic, tàctic i operatiu. Es tracta d'una relació estructurada entre els paradigmes lean, àgil, sostenible, resilient i flexible per a millorar el rendiment de les cadenes de subministrament mitjançant l'aplicació de les tecnologies facilitadores d'I4.0. Basat en això, es proposa un model matemàtic d'optimització lineal entera-mixta, denominat LSCP 4.0, per a maximitzar els beneficis i planificar simultàniament la producció, inventari de materials i productes acabats satisfent la demanda provinent de previsions i comandes en ferma en una cadena de subministrament de cinc nivells. Novament, es combinen enfocaments de producció de just in time (JIT) i planificació de requeriments de materials (MRP). Tots dos models per a LSCP 4.0, i.e., conceptual i matemàtic, es validen en casos d'estudi reals de la indústria de calçat. Addicionalment, es considera l'ús d'una altra tecnologia facilitadora de la I4.0 com la computació en núvol per a abordar el problema de l'intercanvi d'informació entre els nodes de la cadena de subministrament. Així, es proposa un model de dades normalitzat per a la fabricació col·laborativa en el núvol aplicat a la indústria del calçat. / [EN] Innovation in working methods with new lean, sustainable and resilient production systems, as well as effective technology management, are current trends to improve performance in organisations. This PhD thesis investigates the theoretical contributions and formulates a conceptual model with the use of lean manufacturing (LM) and Industry 4.0 (I4.0) tools for production planning processes in supply chains (SCs). In addition, optimisation is employed as an enabling technology of I4.0 to develop the proposed solution. The applied methodology is bibliographic, exploratory and experimental; operational research techniques, data standardisation and case studies in industrial companies are applied. As a starting point, the existing literature related to LM and I4.0 technologies in the SC context is reviewed. Then a conceptual model, known as LSCP 4.0, is designed to facilitate decision making at the strategic, tactical and operational decision levels. It is a structured relation among lean, agile, sustainable, resilient and flexible paradigms to improve SCs' performance via the application of I4.0 enabling technologies. Based on this, an integer-mixed linear optimisation mathematical model, termed LSCP 4.0, is proposed to maximise profits and to simultaneously plan production, material inventory and finished goods by satisfying the demand from forecasts and firm orders in a five-tier SC. Novel just-in-time (JIT) production and material requirements planning (MRP) approaches are combined. Both models for LSCP 4.0, i.e., conceptual and mathematical, are validated in real case studies from the footwear industry. The use of another I4.0 enabling technology, such as cloud computing, is considered to address the problem of information exchange between SC nodes. Thus a standardised data model for collaborative manufacturing in the cloud applied to the footwear industry is proposed. / This thesis has been developed at the Research Centre on Production Management and Engineering (CIGIP) of the Universitat Politècnica de Valencia, within the framework of the projects: "Industrial Data Services for Quality Control in Smart Manufacturing (i4Q)" funded by the European Union H2020 Programme with grant agreement No. 958205; the MCIN/AEI/10.13039/501100011033 and by European Union Next GenerationEU/PRTR with grant agreement PDC2022-133957-100); "Industrial production and loginics optimization in industry 4.0 (i40PT)" funded by the Generalitat Valenciana within the framework of the research groups of excellence project PROMETEO/2021/065; "Optimisation of zero-defects production technologies enabling supply chains 4.0 (CADS4.0)" funded by the Spanish Ministry of Science, Innovation and Universities with grant agreement RTI2018-101344-B-100; "Operational Programme of the European Regional Development Fund (ERDF) of the Autonomous Valencian Community 2014-2020" (Ref. IDIFEDER/2018/025); "Resilient, Sustainable and People-Oriented Supply Chain 5.0 Optimisation Using Hybrid Intelligence" (RESPECT) (Ref. CIGE/2021/159); and a PhD grant from the Technical University of Ambato. / Reyes Vásquez, JP. (2024). Conceptual and optimisation modelling for lean supply chain planning in Industry 4.0 [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/203818 / Compendio

To make a difference among the energy intensive process industries, this dissertation addresses production planning and supply chain planning problems related to industrial energy management issues. The energy issue is turning more and more important from different angles, involving price as well as environmental problems due to climate change leading to political pressure on all energy users. The process industry sector is one of the largest users of energy, and thus important to analyse. Process industries are also capital intensive and operate on large and expensive process equipment, making it imperative to plan their production well in order to reach preferable capacity utilisation. Therefore this dissertation strives to locate the most important energy management issues for the long term profitability of process industries, and investigates the  symbiotic effects of including energy issues in production and supply chain planning. Three different studies at three case companies are carried out, analysed, and presented in five papers. The cases represent the process industry sectors: chemicals, pulp, and steel. Both qualitative case study methodologies as well as quantitative mathematical modelling and optimisation approaches have been practiced. The research questions are analysed from both an energy system and from a production process point of view, separately as well as combined. Energy is somewhat considered to be the main workforce for process industries and this dissertation exemplifies some of its most important dimensions in this context. Several prerequisites for putting energy management on the strategic agenda are located in a specialty chemical industry where the importance of introducing a strategic perspective on energy, the way energy is used, and the possibilities of increasing alternative revenue from utilising by- and/or co-products differently are pinpointed. Approaches for including energy issues in planning processes are also suggested in terms of a MILP model for the entire supply chain of a pulp company, including decisions on purchase and transportation of raw maerials, production allocation, energy mix, and distribution. Another example is presented based on the perspectives of economics of scale and lot sizing through economic order quantity principles in a steel company. By using real company data, energy smart approaches in planning and scheduling are developed with respect to the most important intersections between the production processes and their supporting energy system. The accumulated resource intensity and embedded energy could, and probably should, hence be more fairly  reflected in the product price. The research finally shows some possible impact with including energy issues in a production and supply chain planning model. By planning differently, production prioritisations can be done, and it is not only possible without any large investments, but also prosperous with savings on both energy and money within reach. To conclude, planning of production and supply chain has either a direct or an indirect impact on the energy cost-effectiveness of a company. This dissertation argues that such impact also exists in its mutual form, and is very important when the energy issues are large enough, as they often are in the energy intensive process industry sector. Decision makers should thus beware of the short end of the stick that might be  devastating in the long run, but also aware of all the possibilities that can bring success and prosperity when the future begins.