Trotz genauer Produktionsplanung und -steuerung mit modernen Algorithmen beobachtet man in Fabriksystemen immer wieder plötzliche und unvorhergesehene Zusammenbrüche der Materialströme. Erstaunlicherweise scheinen diese Kapazitätseinbrüche nur wenig durch die aktuelle Pufferauslastung beeinflusst zu sein. Um die entsprechenden Effekte zu unterbinden, wird in diesem Aufsatz eine neuartige Strategie zur Selbstorganisation individueller Güter in Transportund Puffersystemen vorgestellt. Durch ein kooperatives („soziales“) Verhalten dieser Güter lassen sich deren gegenseitige Behinderungen reduzieren, was zu einer deutlichen Harmonisierung des Materialflusses in der innerbetrieblichen Logistik führt. Das vorgeschlagene Konzept wird an einer beispielhaften Fabrik illustriert. Im Rahmen eines erfolgreichen Modellprojekts wird seine praktische Umsetzung derzeit bei einem englischen Verpackungshersteller erprobt. / Despite careful production planning and control using modern algorithms, one can repeatedly observe sudden and unpredicted breakdowns of the material flows in factory systems. Surprisingly, these capacity dips are only marginally affected by the current buffer storage level. To enable prevention of these effects, this paper describes a new strategy for the self-organisation of individual goods in material handling systems. Where the behaviour of the individual goods is cooperative (“social”), their mutual hindrances can be reduced, which in turn leads to a noticeable smoothing of the intra-plant material flows. The suggested concept will be illustrated with a factory example. Its practical applicability is currently being tested within the scope of a successful pilot project with a packaging manufacturer.

The competition in the manufacturing industry has never been higher. Owing to the technological changes and advancements in the market, readily available data is no longer a thing of the past. Numerous studies have discussed the impact of industry 4.0, digital transformation as well as better production planning methods in the manufacturing industry.  The Mass-Manufacturing industry, in specific, has gained efficiency levels in production that were previously unimaginable. Industry 4.0 has been discussed as the ‘next big thing’ in the manufacturing context. In fact, it is seen as a necessity for manufacturing companies to stay competitive. However, efficient production planning methodologies are a preliminary requirement in order to successfully adopt the new manufacturing paradigms. The Engineering-to-order (ETO) industry is still widely unexplored by the academia ETO industries, barely have any production planning methodologies to rely on owing to their complex production processes and high reliance on manual-labour. Regression techniques have repeatedly been used in the production planning context. Considering its statistical prowess, it is no surprise that even the newer machine-learning techniques are based on regression. Considering its success in the mass-manufacturing industry for production planning, is it possible that its usage in the ETO industry might lead to the same results? This thesis involves a case study that was performed at an electrical transformer manufacturing plant in Sweden. After understanding the several operations that are performed in the production process, regression techniques are employed to estimate man-hours. The results from the study reconfirm the statistical prowess of regression and show the possibility of using regression in order to estimate man-hours in the ETO industry. In addition, several factors that can affect successful adoption of this tool in the production planning context are discussed. It is hoped that this study will lay the foundation for better production planning methodologies for the ETO industries in the future which might subsequently result in more data-driven decision making rather than instincts.

El presente proyecto de investigación se basa en la situación actual que se percibe en las micros y pequeñas empresas productoras de Palta Hass del sector agrícola de Ica, Perú. Para ella se pretende presentar el diseño del proceso de planeamiento y control de la producción, perteneciente a un Sistema de Gestión basado en la Gestión por Procesos, que sirve como guía para las pequeñas empresas agrícolas productoras de palta Hass. Una revisión literaria y una investigación de campo se llevaron a cabo para la elaboración de esta propuesta, analizando las necesidades de la forma actual de trabajo de este sector. La metodología en la que se basa este diseño es la administración de procesos, esto permite analizar los procesos existentes en la producción agrícola y, definir y organizar los procesos necesarios para la buena realización del producto. A continuación, se presentará la propuesta de diseño, en conjunto a los procedimientos y los indicadores necesarios para el correcto funcionamiento de la propuesta de planeamiento y control productivo, desarrollado a lo largo de cinco capítulos, en donde se encuentra la recopilación de información, el levantamiento de información estadística, el desarrollo y diseño de la propuesta, la validación por expertos, y las principales conclusiones y recomendaciones del proyecto. Al concluir con el desarrollo del proyecto, se determinó que el presente modelo es una herramienta viable para ser implementada en las micros y pequeñas empresas productoras de palta Hass y que estas logren mejorar su productividad, incrementen sus ventas y logren madurar como empresas. / This Project of investigation is based on the actual situation that is perceived in micro and small companies, producers of Hass Avocado of the agriculture area in Ica, Peru. For that it is pretended to present the design of the process of planning and control of the production belonging to a Management System based on the Management for Process that is used as a guide for the small agricultural companies’ producers of Hass Avocado. A literary revision and an investigation of the field were done for the elaboration of this proposal, analyzing the needs of the current way of work in this area. The methodology in which this design is based is the management of process, this allow analyze the process that are in the agricultural production and, to define and organize the existing process needed for a good realization of the product. Then, a proposal of a design will be presented with a group of procedure and indicators necessary for the correct function Of the proposal of planning and productive control, developed along five chapters, where the compilation of information is found, the raising of statistics information, the development and design of the proposal, validation by experts, and the main conclusions and recommendations of the project. At the end of the development of the project, it was determined that the present model is a viable tool to be implemented en the micro and small companies of Hass Avocado and that they achieve to improve its productivity, increase their sales and mature as companies. / Tesis

Intégrée dans la chaîne décisionnelle de la Supply Chain à un niveau tactique, la Planification de Production est un process clé qui permet de répondre au mieux aux besoins selon les ressources de l’entreprise. Un des défis du domaine est la gestion des incertitudes prévisionnelles, ayant des conséquences importantes sur des indicateurs clés comme le taux de service ou les coûts. Pour y faire face, des méthodes améliorant la flexibilité des processus sont mais en place, comme le contexte de travail en Plan Glissant. Cependant, en actualisant fréquemment les données, la stabilité du système se retrouve dégradée. Ainsi, malgré les gains issus de la gestion des incertitudes, ce cadre crée une complexité dynamique à gérer. Ce travail traite de cette complexité issue de l’actualisation des prévisions pour la planification de production en plan glissant. Plus particulièrement, la question traitée ici concerne l’optimisation du plan de production, en considérant u n système mono-produit monoétage. Une modélisation mathématique générique est tout d’abord développée pour construire un modèle d’optimisation théorique du problème. Ensuite, une procédure de résolution optimale est développée en utilisant le cadre d’optimisation dynamique stochastique. Ce modèle est appliquée à des cas concrets pour lesquels l’optimalité des solutions calculées est prouvée analytiquement grâce à un raisonnement inductif basé sur des séquences de calcul d’espérances mathématiques. Des analyses numériques finalement conduites mettent en exergue les performances de la méthode développée, ses limites, et sa sensibilité vis-à-vis de l’environnement industriel. / Production Planning, as part of tactical operations integrated into the Supply Chain process, is a key procedure allowing decisioners to balance demand and production resources. One of its most challenging issues is to handle uncertainties, especially the ones coming from the Forecasted Demand. In order to manage indicators at stake, such as service level and costs, best practices increasing flexibility in the process are implemented, as Rolling-Plan Framework. However, it creates instability since the updates procedures make the data set on change constantly. Consequently, although the gain in terms of flexibility is non-negligible for the uncertainties management, it generates on the other hand dynamics complexity. We study in this work how to deal this dynamics complexity generated by updates of the Forecasted Demand made in a Rolling-Plan Framework of a Production Planning Process. In particular, the question to which it answers is how to optimize the Production Plan in such a context. This issue is tackled considering a single item single level production system. A general mathematical model in the context of our study is built to be exploitable for analytical optimization. A theoretical optimization framework is designed, and a specific solutions computation framework using stochastic dynamic programming is developed. We apply it in some precise study cases in order to compute optimal solutions and get some valuable analytical results thanks to a dynamic computation process. The optimality of the solutions is proven through an inductive reasoning based on expectations computation. Solutions are finally implemented and calculated numerically with simulations in some particular numerical examples. Analyses and sensitivity studies are performed, highlighting the performances of our optimization method.

Det florerar mycket tankar och funderingar kring varför byggbranschen inte ökat sin produktivitet i samma takt som liknande tillverkningsindustrier och branscher. Det är inte enkelt att sätta fingret på var grunden till problemet ligger. Men det finns faktorer som går att urskilja där produktionen går trögare fram än andra. Två av dessa ska undersökas i denna rapport vilket är kommunikation och produktionsplanering i utförandeskedet.  Studien analyserar hur produktionsplanering och kommunikationsplanen fungerar idag och vilka metoder som används i byggbranschen inom dessa områden. Detta med syftet att förbättra metoderna, för att öka produktiviteten i ett av de stadierna av byggbranschen där det brister som mest, utförandeskedet. Att genom detta minimera slöseri i form av tid, material och energi, samt öka både effektiviteten och produktiviteten i ett byggprojekt.  Metodiken för datainsamlingen har bestått av fallstudier. För att möjliggöra studien har ett byggföretag bidragit med intervjuobjekt från fem av deras byggprojekt, där de svarat på kvantitativa enkäter och kvalitativa intervjuer om sina arbetsplatser. Betoningen har varit studieobjektens egna upplevelser inom effektivitet och produktivitet. Enkät- och intervjudeltagarna var mitt i utförandeskedet och har arbetsroller som platschef, arbetsledare och hantverkare.  Resultatet visar att det aktuella Byggföretaget har välarbetade och strukturerade mallar och metoder för produktionsplanering, men inte lika strukturerade kommunikationsplaner. Genom enkäterna och intervjuerna framgick att kommunikation och produktionsplanering är de faktorer som brister inom organisationen och att det gemensamt fanns ett uttryckt behov till förbättring. Den tydligaste bristen har varit avsaknaden av struktur gällande kommunikation samt att de metoder som tänkt användas för produktionsplaneringen inte implementeras i den grad som det är tänkt. Det framgick även att arbetsplatserna arbetar olika, trots att de ingår i samma organisation. De fungerar som flera mindre företag inom företaget i sin helhet. Det gör att avsaknaden av en tydlig struktur påverkade både produktionsplaneringen och kommunikationen. Detta visade sig vara utmanande för hantverkare vid resursförflyttning, då de måste ändra arbetsmetoder och vänja sig vid en ny struktur. De metoder och mallar som finns tillgängliga, och som i vissa fall är obligatoriska, har tydliga instruktioner hur exempelvis mötesformer och arbetsberedningar ska gå till. Detta för att alla ska känna att Byggföretaget arbetar likadant oavsett vilken arbetsplats inom företaget det gäller, även för underentreprenörer.  Som ett förslag till en lösning som ska vara heltäckande, är det i de pågående projekten svårt att göra några direkta förändringar för att påverka slutresultatet. Däremot vid nästa projekt som startar, så krävs en projektplanering som följs mer i detalj, där inte arbetsplatserna gör egna justeringar, utan följer de direktiv som både är obligatoriska och riktlinjer. Samma grundläggande åtgärder behöver ske kring kommunikationen. En tydlig kommunikationsplan bör inrättas, utformad av en projektgrupp inkluderande samtliga discipliner inkluderat i studien. Det bör även övergripande införas en digitalisering i samtliga led, och inte endast en kommunikationskanal för tjänstemännen. Detta kommer i sin tur kräva att minst arbetsledare får tillgång till en handhållen mobil enhet till sitt förfogande. / The construction industry has been struggling to match the productivity growth seen in similar manufacturing sectors, leading to speculation about the underlying reasons. This report focuses on two factors: communication and production planning during the execution phase. The objective is to analyze current practices and methods with the aim of improving them to enhance productivity.  The study adopts a case study approach, collaborating with a construction company and examining five of their ongoing projects. Quantitative surveys and qualitative interviews were conducted with individuals in key roles such as site managers, supervisors, and craftsmen, to understand their perspectives on current issues.  The results highlight that while the company possesses well-developed and structured production planning methodologies, their communication plans lack similar organization. The findings indicate common deficiencies in communication and production planning, along with an expressed need for improvement. The most evident shortcoming was the absence of structured communication and the incomplete implementation of planned production methods.  Additionally, despite belonging to the same organization, the individual worksites operated as independent entities, which impacted both production planning and communication. These challenges were particularly apparent during resource reallocation, requiring craftsmen to adapt to new work methods and structures. The existing tools and templates, some of which are mandatory, provide clear instructions for processes such as meetings and work preparations, ensuring consistency across different worksites.  As a comprehensive solution, this report recommends enforcing stricter adherence to project plans in upcoming projects, minimizing adjustments made by individual worksites. Additionally, a well-defined communication plan should be established, designed by a project group consisting of all relevant disciplines included in the study. Overall, introducing digitalization across all levels, rather than limiting it to management communication channels, is crucial. Accomplishing this will necessitate providing handheld mobile devices to at least the supervisors to facilitate effective communication and collaboration.

The scheduling of the converter aisle of a nickel smelting plant is a non-trivial task with significant consequences to plant profitability and production. An optimization-based scheduling formulation is developed using a continuous-time paradigm to accurately represent event timings. The formulation accounts for environmental restrictions on sulfur dioxide emissions using event timing constraints. The formulation includes novel semi-continuous modeling to represent flash furnaces which operate with a continuous inlet flow and intermittent discrete material removal, as well as, a novel sequencing and symmetry-breaking scheme to account for identical units operating in parallel. A rolling horizon feature is included in the formulation to accommodate multi-period optimization. Tightening constraints are developed and used to improve the computational performance of the optimization and demonstrate the capacity of the proposed methodology to function as a real-time decision-support tool. A solution procedure is presented where an aggregate model is used to bound the objective function of the master problem in a two layer optimization scheme. Finally, a novel multi-tiered procedure is presented to enhance the optimization solution by re-optimizing for objectives of decreasing priority in order to minimize task start times and penalize deviations in the furnace flow rate. To address the closed-loop properties of scheduling, a reactive scheduling mechanism is included to allow for rescheduling to account the impact of process disturbances on the operating schedule. A methodology for reducing radical scheduling changes due to the optimization during reactive scheduling is presented. The reactive scheduling algorithm utilizes a tiered optimization approach that progressively increases the degrees of freedom available, as required, in order to achieve a feasible production schedule. The use of the reactive scheduling algorithm demonstrates the ability to reject disturbances and transition plant operation in an agile manner. / Thesis / Master of Applied Science (MASc)

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.

Including the inherent temporal variability in a production system in planning and control processes can ensure the fulfillment of the production schedule and increase key performance indica- tors. This benefits the sustainable and efficient use of the system. The current lack of consideration of this inherent temporal variability in production planning leads to optimistic estimates and calcu- lations of planned values that cannot be met. To complete this information, the inherent temporal variability in a production system is investigated using a systematic approach. This approach detects, identifies, and quantifies inherent temporal variability and is applied to a data base created via an automated, event-driven procedure. The approach is tested in a smart factory laboratory. The results to date on improving production planning and control are promising as key performance indicators have been increased. There is still a need for action to ensure the fulfillment of the production schedule. Concluding, work on this topic has just begun, as can be seen from the discussion section. More data need to be collected and aggregated for future research. This publication is intended to motivate researchers to address this issue and better manage the existing uncertainty in production through the use of data.

Artificial Intelligence (AI) has proven to be highly suitable for a wide range of problems in manufacturing environments, including the prediction of lead times. Most of these solutions are based on ”black-box” algorithms, which hinder practitioners to understand the prediction process. Explainable Artificial Intelligence (XAI) provides numerous tools and methods to counteract this problem. There is however a need to qualify the methods with human-centered studies in manufacturing environments, since explainabilityis context-specific. The purpose of this mixed-method case study is to examine the explainability of regression models for lead time prediction in quality control laboratories at a biopharmaceutical production site in Sweden. This entails the research questions of which methods can increase the explainability of lead time prediction, what type of explanation is required to enable explainability and what are the benefits of explaining regression models in this context. This is why relevant literature in the field of XAI and AI-based lead time prediction is reviewed. An explainable lead time prediction modelis developed and a Delphi study is carried out to gauge the importance of different explanation types and to identify explainability-related benefits. The results show a transparency-performance trade-off and highlight eight benefits that are mapped to the model’s life cycle. These findings provide new insights into the explainability requirements and benefits in quality control processes and support practitioners in steering their implementation efforts. / Artificiell Intelligens (AI) har visat sig vara mycket lämplig för ett stort antal problem i tillverkningsmiljöer, bland annat när det gäller att förutsäga ledtider. De flesta av dessa lösningar är baserade på algoritmer som är ”svarta lådor”, vilket gör det svårt för tillämparna att förstå förutsägelseprocessen. Explainable Artificial Intelligence (XAI) erbjuder många verktyg och metoder för att motverka detta problem. Det finns dock ett behov av att kvalificera metoderna med människocentrerade studier i tillverkningsmiljöer, eftersom förklarbarhet är kontextspecifikt. Syftet med denna fallstudie med blandad metod är att undersöka förklaringsbarheten hos regressionsmodeller för prediktion av ledtider i kvalitets kontrolllaboratorier vid en biopharmaceutisk produktionsanläggning i Sverige. Vilket syftar till forskningsfrågorna samt vilka metoder som kan öka förklaringsbarheten och av prognoser för ledtider, vilken typ av förklaring som krävs för att möjliggöra en förklarbarhet och vilka fördelar som finns med att förklara regressionsmodeller i detta sammanhang. Det är därför som relevant litteratur på området XAI och AI baserade prognostisering av ledtider granskas. En förklaringsbar modell för prognostisering av ledtider utvecklas och en Delphi-studie genomförs för att bedöma betydelsen av olika typer av förklaringar och för att identifiera förklaringsrelaterade fördelar.

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