Methodological approach to study the dynamics of production networks: Discrete-event simulation modelling

This paper shows how discrete-event simulation represents an appropriate tool for approaching the dynamics of production networks. Three important factors influencing production network dynamics, specifically finite production capacity, manufacturing lead time, and its variability are discussed and a basic discrete-event simulation model is presented. Such model, which in its basic form represents a simple retail/distribution two-stage supply chain, is then extended in order to take into account those factors that can not be included in a classical control theoretical model

Determining Kanban Size Using Mathematical Programming and Discrete Event Simulation for a Manufacturing System with Large Production Variability

In order to become more competitive and aggressive in the market place it is imperative for manufacturers to reduce cycle time, limit work-in-process, and improve productivity, responsiveness, capacities, and quality. One manner in which supply chains can be improved is via the use of kanbans in a pull production system. Kanbans refer to a card or signal for productions scheduling within just-in-time (JIT) production systems to signal where and what to produce, when to produce it, and how much. A Kanban based JIT production system has been shown to be beneficial to supply chains for they reduce work-in-process, provide real time status of the system, and enhance communication both up and down stream. While many studies exist in regards to determining optimal number of kanbans, types of kanban systems, and other factors related to kanban system performance, no comprehensive model has been developed to determine kanban size in a manufacturing system with variable workforce production rate and variable demand pattern. This study used Stewart-Marchman-Act, a Daytona Beach rehabilitation center for those with mental disabilities or recovering from addiction that has several manufacturing processes, as a test bed sing mathematical programming and discrete event simulation models to determine 2 the Kanban size empirically. Results from the validated simulation model indicated that there would be a significant reduction in cycle time with a kanban system; on average, there would be a decrease in cycle time of nine days (almost two weeks). Results were discussed and limitations of the study were presented in the end

Proceedings of the third International Workshop of the IFIP WG5.7

Contents of the papers presented at the international workshop deal with the wide variety of new and computer-based techniques for production planning and control that has become available to the scientific and industrial world in the past few years: formal modeling techniques, artificial neural networks, autonomous agent theory, genetic algorithms, chaos theory, fuzzy logic, simulated annealing, tabu search, simulation and so on. The approach, while being scientifically rigorous, is focused on the applicability to industrial environment

Introduction to Production: Philosophies, Flow, and Analysis

Production is a fundamental societal and economic activity. Production has to do with the transformation of raw materials into useful objects and includes the knowledge to complete the transformation effectively. Thus, production is a board topic ranging from philosophies about how to approach production such as lean and quick response manufacturing, how to organize production facilities, how to analyze production operations, how to control the flow of materials during production, the devices used to move materials within a facility, and strategies for coordinating multiple production facilities. An integrated introduction to production is presented in a set of learning modules. In significant part, these learning modules are based on over 20 years of interactions with the professional production community in the West Michigan region where Grand Rapids and Holland are the principal cities. This community consists almost exclusively of small and medium size companies engaged primarily in high mix, low volume manufacturing. Students in the Bachelor of Science in Engineering and Master of Science in Engineering programs at Grand Valley State University often work in production for these companies. Thus, interactions are facilitated particularly though master’s degree capstone projects, several of which are referenced in the learning modules. The learning modules are well-grounded in established production concepts. Emphasis is placed on proven procedures such as systematic layout planning, factory physics, various production flow control techniques such as kanban and POLCA, and discrete event simulation. Professional practice is a focus of the learning modules. Material from processional groups such as the Lean Enterprise Institute and the Material Handling Institute (MHI) is integrated. The opportunity to read and discuss professional publications presenting production improvement projects is provided. Students are referred to professional videos and web sites throughout the learning modules. All materials provided are referenced are open access and free of charge. When downloading the main file, it is important to also download and use the Main File Support as it contains supplemental materials.https://scholarworks.gvsu.edu/books/1022/thumbnail.jp

Modelling flexible manufacturing systems through discrete event simulation

As customisation and product diversification are becoming standard, industry is looking for strategies to become more adaptable in responding to customer’s needs. Flexible manufacturing systems (FMS) provide a unique capability where there is a need to provide efficiency through production flexibility. Full potential of FMS development is difficult to achieve due to the variability of components within this complex manufacturing system. It has been recognised that there is a requirement for decision support tools to address different aspects of FMS development. Discrete event simulation (DES) is the most common tool used in manufacturing sector for solving complex problems. Through systematic literature review, the need for a conceptual framework for decision support in FMS using DES has been identified. Within this thesis, the conceptual framework (CF) for decision support for FMS using DES has been proposed. The CF is designed based on decision-making areas identified for FMS development in literature and through industry stakeholder feedback: set-up, flexibility and schedule configuration. The CF has been validated through four industrial simulation case studies developed as a part of implementation of a new FMS plant in automotive sector. The research focuses on: (1) a method for primary data collection for simulation validated through a case study of material handling robot behaviour in FMS; (2) an approach for evaluation of optimal production set-up for industrial FMS with DES; (3) a DES based approach for testing FMS flexibility levels; (4) an approach for testing scheduling in FMS with the use of DES. The study has supported the development of systematic approach for decision making in FMS development using DES. The approach provided tools for evidence based decision making in FMS

Selection of simulation tools for improving supply chain performance

Simulation is an effective method for improving supply chain performance. However, there is limited advice available to assist practitioners in selecting the most appropriate method for a given problem. Much of the advice that does exist relies on custom and practice rather than a rigorous conceptual or empirical analysis. An analysis of the different modelling techniques applied in the supply chain domain was conducted, and the three main approaches to simulation used were identified; these are System Dynamics (SD), Discrete Event Simulation (DES) and Agent Based Modelling (ABM). This research has examined these approaches in two stages. Firstly, a first principles analysis was carried out in order to challenge the received wisdom about their strengths and weaknesses and a series of propositions were developed from this initial analysis. The second stage was to use the case study approach to test these propositions and to provide further empirical evidence to support their comparison. The contributions of this research are both in terms of knowledge and practice. In terms of knowledge, this research is the first holistic cross paradigm comparison of the three main approaches in the supply chain domain. Case studies have involved building ‘back to back’ models of the same supply chain problem using SD and a discrete approach (either DES or ABM). This has led to contributions concerning the limitations of applying SD to operational problem types. SD has also been found to have risks when applied to strategic and policy problems. Discrete methods have been found to have potential for exploring strategic problem types. It has been found that discrete simulation methods can model material and information feedback successfully. Further insights have been gained into the relationship between modelling purpose and modelling approach. In terms of practice, the findings have been summarised in the form of a framework linking modelling purpose, problem characteristics and simulation approach

REAL-TIME LOGISTICS - Case Development of a Shipment Status Display System for a Large Manufacturing Company

As traditional heavy industry businesses transform into global solutions providers, their business models change into project-based and their supply networks expand. Project business faces greater uncertainty within the supply chain than traditional business, thus requires greater need for data exchange within the supply chain. Numerous information systems have provided the organization with a wealth of data. However project management often faces great challenges to utilize it for better visibility on project delivery status, as well as to communicate that to stakeholders. In response to the need for better usage and presentation of transactional project logistical data, a real-time shipment status display system has been developed. The complete system offers an intuitive, up-to-date, fast, and reliable display that is accessible through a wide range of devices. In this thesis, the system is customized to run on public displays. In term of development methodology, spiral axiomatic design approach is adopted to ensure maximum independence of components. The end result is a system comprising of two independent sub-systems: one is for data collection and the second one is for presentation. Modern web technologies such as ASP.NET MVC4, HTML5, and CSS3 have been used to develop the presentation sub-system. The thesis contributes a software artifact that complements information systems that are either too much focused on transactional data or unable to communicate project logistics data to stakeholders. It also demonstrates the use of axiomatic system design in developing modern web platforms.fi=Opinnäytetyö kokotekstinä PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=Lärdomsprov tillgängligt som fulltext i PDF-format

Implementing Industry 4.0 in SMEs

This open access book addresses the practical challenges that Industry 4.0 presents for SMEs. While large companies are already responding to the changes resulting from the fourth industrial revolution , small businesses are in danger of falling behind due to the lack of examples, best practices and established methods and tools. Following on from the publication of the previous book ‘Industry 4.0 for SMEs: Challenges, Opportunities and Requirements’, the authors offer in this new book innovative results from research on smart manufacturing, smart logistics and managerial models for SMEs. Based on a large scale EU-funded research project involving seven academic institutions from three continents and a network of over fifty small and medium sized enterprises, the book reveals the methods and tools required to support the successful implementation of Industry 4.0 along with practical examples