Integrated Resource Allocation and Scheduling in Bidirectional Flow Shop with Multi-Machine and COS Constraints

10.1109/TSMCC.2008.2007500IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews392190-200ITCR

Evaluating the performance of an AGV fleet in an FMS under minimizing part movement and balancing workload rules

The performance of an FMS with respect to AGV utilization is assessed using a simulation model. AGV fleets of different sizes are evaluated. Under OOM, an assignment rule designed to decrease time in system by minimizing part movements among machine tools, AGV utilization is lower than under WINO, an assignment rule that seeks to balance machine workload. For a given AGV fleet, machine utilization imbalance is more levelled under WINO than OOM, however comparing across the three AGV fleets, the maximum machine imbalance is smoother under OOM than under WINO. AGV utilization consistently decreases as the number of AGVs increases from eight to nine and then to 10. The system performance is adversely affected not only by too many AGVs but also by surplus spots in both inbound and outbound queues placed in front of the machine tools

Production Scheduling

Generally speaking, scheduling is the procedure of mapping a set of tasks or jobs (studied objects) to a set of target resources efficiently. More specifically, as a part of a larger planning and scheduling process, production scheduling is essential for the proper functioning of a manufacturing enterprise. This book presents ten chapters divided into five sections. Section 1 discusses rescheduling strategies, policies, and methods for production scheduling. Section 2 presents two chapters about flow shop scheduling. Section 3 describes heuristic and metaheuristic methods for treating the scheduling problem in an efficient manner. In addition, two test cases are presented in Section 4. The first uses simulation, while the second shows a real implementation of a production scheduling system. Finally, Section 5 presents some modeling strategies for building production scheduling systems. This book will be of interest to those working in the decision-making branches of production, in various operational research areas, as well as computational methods design. People from a diverse background ranging from academia and research to those working in industry, can take advantage of this volume

Scheduling With Alternatives Machine Using Fuzzy Inference System And Genetic Algorithm.

As the manufacturing activities in today's industries are getting more and more complex, it is required for the manufacturing company to have a good shop floor production scheduling to plan and schedule their production orders. Industri pengeluarcim kini telah berkembang pesat dan aktiviti pengeluarannya semakin kompleks, dengan itu syarikat pengeluar memerlukan jadual lantai pengeluaran (shop floor) yang terbaik untuk merancang permintaan pengeluaran (product)

A control methodology for automated manufacturing

The application of computers in the manufacturing industry has substantially altered the control procedures used to program a whole manufacturing process. Currently, one the problems which automated manufacturing systems are experiencing is the lack of a good overall control system. The subject of this research has been centred on the identification of the problems involved in current methods of control and their advantages and disadvantages in an automated manufacturing system. As a result, a different type of control system has been proposed which distributes both the control and the decision making. This control model is an hybrid of hierarchical and hierarchical control systems which takes advantage of the best points offered by both types of control structures. The Durham FMS rig has been used as a testbed for an automated manufacturing system to which the hybrid control system has been applied. The implementation of this control system would not have been possible without the design and development of a System Integration Tool (SIT). The system is capable of real-time scheduling of the system activities. Activities within the system are monitored in real-time and a recording of the system events is available, which allows the user to analyse the activities of the system off-line. A network independent communication technique was developed for the Durham FMS which allowed the manufacturing cells to exercise peer-to-peer communication. The SIT also allowed the integration of equipment from different vendors in the FMS

Heuristic scheduling algorithms for dedicated and flexible manufacturing systems

Imperial Users onl

A new model and metaheuristic approach for the energy-based resource-constrained scheduling problem

[EN] This article focuses on obtaining sustainable and energy-efficient solutions for limited resource programming problems. To this end, a model for integrating makespan and energy consumption objectives in multi-mode resource-constrained project scheduling problems (MRCPSP-ENERGY) is proposed. In addition, a metaheuristic approach for the efficient resolution of these problems is developed. In order to assess the appropriateness of theses proposals, the well-known Project Scheduling Problem Library is extended (called PSPLIB-ENERGY) to include energy consumption to each Resource-Constrained Project Scheduling Problem instance through a realistic mathematical model. This extension provides an alternative to the current trend of numerous research works about optimization and the manufacturing field, which require the inclusion of components to reduce the environmental impact on the decision-making process. PSPLIB-ENERGY is available at http://gps.webs.upv.es/psplib-energy/.The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by the Spanish Government under the research projects TIN2013-46511-C2-1 and TIN2016-80856-R.Morillo-Torres, D.; Barber, F.; Salido, MA. (2017). A new model and metaheuristic approach for the energy-based resource-constrained scheduling problem. Proceedings of the Institution of Mechanical Engineers Part B Journal of Engineering Manufacture. 1(1):1-13. https://doi.org/10.1177/0954405417711734S1131

Working Notes from the 1992 AAAI Spring Symposium on Practical Approaches to Scheduling and Planning

The symposium presented issues involved in the development of scheduling systems that can deal with resource and time limitations. To qualify, a system must be implemented and tested to some degree on non-trivial problems (ideally, on real-world problems). However, a system need not be fully deployed to qualify. Systems that schedule actions in terms of metric time constraints typically represent and reason about an external numeric clock or calendar and can be contrasted with those systems that represent time purely symbolically. The following topics are discussed: integrating planning and scheduling; integrating symbolic goals and numerical utilities; managing uncertainty; incremental rescheduling; managing limited computation time; anytime scheduling and planning algorithms, systems; dependency analysis and schedule reuse; management of schedule and plan execution; and incorporation of discrete event techniques

A Digital Twin Framework for Production Planning Optimization: Applications for Make-To-Order Manufacturers

In this dissertation, we develop a Digital Twin framework for manufacturing systems and apply it to various production planning and scheduling problems faced by Make-To-Order (MTO) firms. While this framework can be used to digitally represent a particular manufacturing environment with high fidelity, our focus is in using it to generate realistic settings to test production planning and scheduling algorithms in practice. These algorithms have traditionally been tested by either translating a practical situation into the necessary modeling constructs, without discussion of the assumptions and inaccuracies underlying this translation, or by generating random instances of the modeling constructs, without assessing the limitations in accurately representing production environments. The consequence has been a serious gap between theory advancement and industry practice. The major goal of this dissertation is to develop a framework that allows for practical testing, evaluation, and implementation of new approaches for seamless industry adoption. We develop this framework as a modular software package and emphasize the practicality and configurability of the framework, such that minimal modelling effort is required to apply the framework to a multitude of optimization problems and manufacturing systems. Throughout this dissertation, we emphasize the importance of the underlying scheduling problems which provide the basis for additional operational decision making. We focus on the computational evaluation and comparisons of various modeling choices within the developed frameworks, with the objective of identifying models which are both effective and computationally efficient. In Part 1 of this dissertation, we consider a class of Production Planning and Execution problems faced by job shop manufacturing systems. In Part 2 of this dissertation, we consider a class of scheduling problems faced by manufacturers whose production system is dominated by a single operation