Supply chain design considering cellular structure and alternative processing routings

Nowadays, in highly competitive global markets and constant pressure to reduce total costs, enterprises consider group technology and Supply Chain Management (SCM) accordingly and usually separately as the key elements for intra and inter facilities improvement. Simultaneous consideration of the elements of these two disciplines in an integrated design can result in higher efficiency and effectiveness. A three-echelon supply chain that has several markets, production sites, and suppliers is designed again in this paper as a Cellular Manufacturing System (CMS). Every product can be manufactured in the CMS through alternative process routings, in which machines are likely to fail. A linear integer programming model is presented here that seeks to minimize the intercellular movement, procurement, production, and machine breakdown costs. We present a number of illustrative examples to demonstrate the effectiveness of the integrated design. The proposed examples reveal that although the procurement and logistics costs increase slightly in the integrated design, the total cost is dropped considerably

Cell forming and cell balancing of virtual cellular manufacturing systems with alternative processing routes using genetic algorithm

Cellular manufacturing (CM) is one of the most important subfields in the design of manufacturing systems and as a recently emerged field of study and practice, virtual cellular manufacturing (VCM) inherits the importance from CM. One type of VCM problems is VCM with alternative processing routes from which the route for processing each part should be selected. In this research, a bi-objective mathematical programming model is designed in order to obtain optimal routing of parts, the layout of machines and the assignment of cells to locations and to minimize the production costs and to balance the cell loads. The proposed mathematical model is solved by multi-choice goal programming (MCGP). Since CM models are NP-Hard, a genetic algorithm (GA) is utilized to solve the model for large-sized problem instances and the results obtained from both methods are compared. Finally, a conclusion is made and some visions for future works are offered.Cellular manufacturing (CM) is one of the most important subfields in the design of manufacturing systems and as a recently emerged field of study and practice, virtual cellular manufacturing (VCM) inherits the importance from CM. One type of VCM problems is VCM with alternative processing routes from which the route for processing each part should be selected. In this research, a bi-objective mathematical programming model is designed in order to obtain optimal routing of parts, the layout of machines and the assignment of cells to locations and to minimize the production costs and to balance the cell loads. The proposed mathematical model is solved by multi-choice goal programming (MCGP). Since CM models are NP-Hard, a genetic algorithm (GA) is utilized to solve the model for large-sized problem instances and the results obtained from both methods are compared. Finally, a conclusion is made and some visions for future works are offered

Multi-Agent Systems

A multi-agent system (MAS) is a system composed of multiple interacting intelligent agents. Multi-agent systems can be used to solve problems which are difficult or impossible for an individual agent or monolithic system to solve. Agent systems are open and extensible systems that allow for the deployment of autonomous and proactive software components. Multi-agent systems have been brought up and used in several application domains

Period Batch Control - A Production Planning System Applied to Virtual Manufacturing Cells

Period Batch Control (PBC) system has been known for its implementation with the classical group technology (GT) cells, and it has been known for its simplicity. The main production planning decisions concern the choice of the period length and the stage number and contents. Also, in order to better integrate the production planning with the application of GT cells at the shop floor, the concept of virtual manufacturing cells has been applied. Since virtual cells configurations are changing periodically, a model for implementing the PBC system into virtual manufacturing cells environment is developed. The model enables alignment of the PBC principles and rules with virtual cell design goals. Model is tested on the case study of furniture production. With the use of scheduling software, different scheduling rules were simulated for four production weeks. The experimental results from these for production weeks show how the choice of PBC parameters impacts the virtual cells configurations, machine sharing and utilization

Best matching processes in distributed systems

The growing complexity and dynamic behavior of modern manufacturing and service industries along with competitive and globalized markets have gradually transformed traditional centralized systems into distributed networks of e- (electronic) Systems. Emerging examples include e-Factories, virtual enterprises, smart farms, automated warehouses, and intelligent transportation systems. These (and similar) distributed systems, regardless of context and application, have a property in common: They all involve certain types of interactions (collaborative, competitive, or both) among their distributed individuals—from clusters of passive sensors and machines to complex networks of computers, intelligent robots, humans, and enterprises. Having this common property, such systems may encounter common challenges in terms of suboptimal interactions and thus poor performance, caused by potential mismatch between individuals. For example, mismatched subassembly parts, vehicles—routes, suppliers—retailers, employees—departments, and products—automated guided vehicles—storage locations may lead to low-quality products, congested roads, unstable supply networks, conflicts, and low service level, respectively. This research refers to this problem as best matching, and investigates it as a major design principle of CCT, the Collaborative Control Theory. The original contribution of this research is to elaborate on the fundamentals of best matching in distributed and collaborative systems, by providing general frameworks for (1) Systematic analysis, inclusive taxonomy, analogical and structural comparison between different matching processes; (2) Specification and formulation of problems, and development of algorithms and protocols for best matching; (3) Validation of the models, algorithms, and protocols through extensive numerical experiments and case studies. The first goal is addressed by investigating matching problems in distributed production, manufacturing, supply, and service systems based on a recently developed reference model, the PRISM Taxonomy of Best Matching. Following the second goal, the identified problems are then formulated as mixed-integer programs. Due to the computational complexity of matching problems, various optimization algorithms are developed for solving different problem instances, including modified genetic algorithms, tabu search, and neighbourhood search heuristics. The dynamic and collaborative/competitive behaviors of matching processes in distributed settings are also formulated and examined through various collaboration, best matching, and task administration protocols. In line with the third goal, four case studies are conducted on various manufacturing, supply, and service systems to highlight the impact of best matching on their operational performance, including service level, utilization, stability, and cost-effectiveness, and validate the computational merits of the developed solution methodologies

Assessment of shop floor layouts in the context of process plans with alternatives

Paper aims: The paper seeks to compare the performance of three layouts in a make to order (MTO) production system with high product variability. Originality: No previous work sought to compare job shop, cellular and virtual cell layouts in an MTO system with high product variability, with just 21 resources, a low amount. The analysis considered models with the same capacities and demand for the three layouts. Research method: The complete factorial design and ANOVA were used with simulation. The main effects plots of the control factors for response variables were obtained (e.g. throughput, lead time, and resource utilization). Main findings: The virtual cell layout had results similar to the job shop, but achieved better outcomes compared with the traditional cell. Implications for theory and practice: The knowledge gap regarding virtual cells signals the importance of this topic, as well as the possibilities not yet investigated about it in manufacturing companies.</br

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