Design and Management of Manufacturing Systems

Although the design and management of manufacturing systems have been explored in the literature for many years now, they still remain topical problems in the current scientific research. The changing market trends, globalization, the constant pressure to reduce production costs, and technical and technological progress make it necessary to search for new manufacturing methods and ways of organizing them, and to modify manufacturing system design paradigms. This book presents current research in different areas connected with the design and management of manufacturing systems and covers such subject areas as: methods supporting the design of manufacturing systems, methods of improving maintenance processes in companies, the design and improvement of manufacturing processes, the control of production processes in modern manufacturing systems production methods and techniques used in modern manufacturing systems and environmental aspects of production and their impact on the design and management of manufacturing systems. The wide range of research findings reported in this book confirms that the design of manufacturing systems is a complex problem and that the achievement of goals set for modern manufacturing systems requires interdisciplinary knowledge and the simultaneous design of the product, process and system, as well as the knowledge of modern manufacturing and organizational methods and techniques

New Approaches for Modeling and Evaluating Agility in Integrated Supply Chains

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An enterprise modeling and integration framework based on knowledge discovery and data mining

This paper deals with the conceptual design and development of an enterprise modeling and integration framework using knowledge discovery and data mining. First, the paper briefly presents the background and current state-of-the-art of knowledge discovery in databases and data mining systems and projects. Next, enterprise knowledge engineering is dealt with. The paper suggests a novel approach of utilizing existing enterprise reference architectures, integration and modeling frameworks by the introduction of new enterprise views such as mining and knowledge views. An extension and a generic exploration of the information view that already exists within some enterprise models are also proposed. The Zachman Framework for Enterprise Architecture is also outlined versus the existing architectures and the proposed enterprise framework. The main contribution of this paper is the identification and definition of a common knowledge enterprise model which represents an original combination between the previous projects on enterprise architectures and the Object Management Group (OMG) models and standards. The identified common knowledge enterprise model has therefore been designed using the OMG's Model-Driven Architecture (MDA) and Common Warehouse MetaModel (CWM), and it also follows the RM-ODP (ISO/OSI). It has been partially implemented in Java(TM), Enterprise JavaBeans (EJB) and Corba/IDL. Finally, the advantages and limitations of the proposed enterprise model are outlined

A Conceptual Framework to Support Digital Transformation in Manufacturing Using an Integrated Business Process Management Approach

Digital transformation is no longer a future trend, as it has become a necessity for businesses to grow and remain competitive in the market. The fourth industrial revolution, called Industry 4.0, is at the heart of this transformation, and is supporting organizations in achieving benefits that were unthinkable a few years ago. The impact of Industry 4.0 enabling technologies in the manufacturing sector is undeniable, and their correct use offers benefits such as improved productivity and asset performance, reduced inefficiencies, lower production and maintenance costs, while enhancing system agility and flexibility. However, organizations have found the move towards digital transformation extremely challenging for several reasons, including a lack of standardized implementation protocols, emphasis on the introduction of new technologies without assessing their role within the business, the compartmentalization of digital initiatives from the rest of the business, and the large-scale implementation of digitalization without a realistic view of return on investment. To instill confidence and reduce the anxiety surrounding Industry 4.0 implementation in the manufacturing sector, this paper presents a conceptual framework based on business process management (BPM). The framework is informed by a content-centric literature review of Industry 4.0 technologies, its design principles, and BPM method. This integrated framework incorporates the factors that are often overlooked during digital transformation and presents a structured methodology that can be employed by manufacturing organizations to facilitate their transition towards Industry 4.0

Modelling business processes with links to ISO 9001

Merged with duplicate record 10026.1/795 on 14.02.2017 by CS (TIS)This work in the domain of quality management and business process design looks at how the requirements of the ISO 9001 standard for quality management systems are designed and implemented in business. It is the aim of the research reported in this thesis to support manufacturing companies when modelling a Fulfil Order Process by identifying the links to the ISO 9001 quality standard and highlighting potential impact from any changes in the process or the standard during a redesign project. It does so by presenting a modelling technique, named IDEF9000, which will enable companies to take a systemic perspective of a Fulfil Order Process identifying all relevant links to ISO 9001. A research strategy based around the experiences of companies when designing business processes with links to ISO 9001 was adopted. In-depth case studies carried out by the author showed that simply documenting what an organisation does to satisfy the various elements of ISO 9001 is still one of the most common approaches adopted. This results in a process-oriented character only at the documentation stage. It is the result of limited guidance on how to integrate the requirements of ISO 900 I in business processes. The work proceeded by exploring the domains of business processes, the use of systems thinking to explain business processes and the relevance of ISO 9001 requirements from a process-based viewpoint. A set of criteria was developed to identify activities, information and other flows controlled by ISO 9001 to design a Fulfil Order Process in a manufacturing company. This provided the context for the development of the modelling technique IDEF9000, which is an enhanced version of IDEFo, and its validation by review and by use in two manufacturing companies. The originality of this work lies in the identification and emphasis by the author of the need to take a systemic view of business processes when designing or redesigning a process-based ISO 9001 quality management system. Also, criteria for a technique to address the modelling of a Fulfil Order Process were identified. Furthermore this contribution to knowledge includes the identification of links between ISO 9001 requirements and a holistic Fulfil Order Process. This led to the development of further criteria for modelling such a business process showing the links to ISO 9001. IDEF9000 represents an improved modelling approach that fulfils the identified criteria and permits the systemic design or redesign of a Fulfil Order Process while establishing the links controlled by the ISO 9001 quality standard

Land-Cover and Land-Use Study Using Genetic Algorithms, Petri Nets, and Cellular Automata

Recent research techniques, such as genetic algorithm (GA), Petri net (PN), and cellular automata (CA) have been applied in a number of studies. However, their capability and performance in land-cover land-use (LCLU) classification, change detection, and predictive modeling have not been well understood. This study seeks to address the following questions: 1) How do genetic parameters impact the accuracy of GA-based LCLU classification; 2) How do image parameters impact the accuracy of GA-based LCLU classification; 3) Is GA-based LCLU classification more accurate than the maximum likelihood classifier (MLC), iterative self-organizing data analysis technique (ISODATA), and the hybrid approach; 4) How do genetic parameters impact Petri Net-based LCLU change detection; and 5) How do cellular automata components impact the accuracy of LCLU predictive modeling. The study area, namely the Tickfaw River watershed (711mi²), is located in southeast Louisiana and southwest Mississippi. The major datasets include time-series Landsat TM / ETM images and Digital Orthophoto Quarter Quadrangles (DOQQ’s). LCLU classification was conducted by using the GA, MLC, ISODATA, and Hybrid approach. The LCLU change was modeled by using genetic PN-based process mining technique. The process models were interpreted and input to a CA for predicting future LCLU. The major findings include: 1) GA-based LCLU classification is more accurate than the traditional approaches; 2) When genetic parameters, image parameters, or CA components are configured improperly, the accuracy of LCLU classification, the coverage of LCLU change process model, and/or the accuracy of LCLU predictive modeling will be low; 3) For GA-based LCLU classification, the recommended configuration of genetic / image parameters is generation 2000-5000, population 1000, crossover rate 69%-99%, mutation rate 0.1%-0.5%, generation gap 25%-50%, data layers 16-20, training / testing data size 10000-20000 / 5000-10000, and spatial resolution 30m-60m; 4) For genetic Petri nets-based LCLU change detection, the recommended configuration of genetic parameters is generation 500, population 300, crossover rate 59%, mutation rate 5%, and elitism rate 4%; and 5) For CA-based LCLU predictive modeling, the recommended configuration of CA components is space 6025 * 12993, state 2, von Neumann neighborhood 3 * 3, time step 2-3 years, and optimized transition rules

Development of a Process Modelling System for Simulation

This thesis details the development of a process modelling technique to aid a simulation model developer during the requirements gathering and conceptual modelling phases of a simulation project. There are a number of process modelling techniques available that are capable of being used during such phases of a simulation project, however there is currently a lack of process modelling techniques developed specifically to aid a simulation model developer in capturing, representing and communicating information and systems issues to persons involved in the operation of discrete systems under investigation. A detailed review of the literature related to techniques capable of supporting the pre-simulation phases of a simulation project is presented. The main conclusion of this review is that there is a specific lack of support available to aid a simulation model developer in the pre-coding phases of a simulation project. Currently there are no process modelling techniques available that specifically support the pre-simulation phases of a discrete event simulation project. To attempt to overcome this shortfall the thesis discusses the development of a process modelling technique specifically developed to support the pre-simulation phases of a simulation project. Objectives in the development of this technique were to develop a technique that: 1. Is capable of capturing a detailed description of a Discrete Event System; 2. Has a low modelling burden and therefore is capable of being used by non specialists; 3. Presents modelling information at a high semantic level so that manufacturing personnel can rationalise with it; 4. Has good visualisation capabilities. The technique developed is called Simulation Activity Diagrams (SADs). To demonstrate the ability of the SAD technique to model discrete event information a prototype process modelling tool, Process Modelling for Simulation (PMS) was developed. An evaluation of the SAD technique is then presented through of a number of real and conceptual discrete event systems used to examine the techniques ability to accurately model information along with its ease of use and modelling accuracy. The thesis concludes that more research is required in validating and developing SADs and in developing other techniques in the pre-simulation area

Towards resilient supply chain networks

In the past decade, events like 9/11 terror attacks, the recent financial crisis and other major crisis has proved that there is strong interaction and interdependency of a supply chain network with its external environments in various channels and thus a need to focus on building resiliency (in short, the ability of the system to recover from damage or disruption) of the entire network system. Although literature has discussed some way of improving resiliency of an individual firm which is a member of the network system, it lacked to capture a holistic view of the supply chain network. Pertaining to this observation, this work proposes to improve resiliency of a supply chain network from a system’s perspective rather concentrate on an individual firm. For this purpose, this thesis proposes a conceptual framework to promote early identification and timely information of the disruptions arising in a supply chain network and timely sharing of this information among all the members of the network. The key principle emphasized in this thesis is that recovery from an inevitable disruption has a better possibility if a member of the supply chain network has an early indication or knowledge of the upcoming disruption. A discrete event dynamic system simulation tool called Petri nets is utilized to realize the proposed conceptual framework. Furthermore, the practical benefits and implications of the proposed model and tool are demonstrated with help of two case studies. This thesis has several contributions to the field of operation management and supply chain. First, a new paradigm for supply chain management to avoid large scale failures such as financial crisis is available to the field, which may be applied by governments or regulatory bodies. Second, a new framework which allows for a quantitative analysis of failures of an entire supply chain network is available to the field, which is easy to be used. Third, a novel application of Petri nets to this new problem in supply chain management is available