Sílvio Carmo Silva

Order release in a workload controlled flow-shop with sequence-dependent set-up times

In this paper, we report a simulation study on the role of sequence-dependent set-up times in decision making at the order release level of a workload controlled make-to-order flow-shop. The study evaluates the potential for set-ups savings, dependent on the level of workload in the shop, for two alternative strategies, namely considering set-up times centrally, within the release decision or locally, within the dispatching decision. These strategies are compared and assessed on the basis of two main performance measures namely time in system and standard deviation of the job lateness. Results indicate that the local strategy, which has been traditionally adopted in practice and in most of the studies dealing with sequence-dependent set-up times, does not always give the best results. The release frequency and the shop workload appear critical to the selection of the strategy to adopt, strongly influencing system performance.

An Ontology For A Model Of Manufacturing Scheduling Problems To Be Solved On The Web

In this paper we describe an ontology for a model of manufacturing scheduling problems to be solved on the web, through several different scheduling methods made available by a web scheduling decision support system. This approach aims enabling to share scheduling knowledge and methods, in a globally distributed context, in order to facilitate solving these problems, either in the industry or in the academic and research context. The proposed ontology is described in terms of basic objects, the scheduling problem attributes, in the form of problems characterization parameters; problem classes or types of scheduling problems and relations among problem classes; and problems instances. Finally, a sample of methods is presented for solving some well known problems arising in the scope of manufacturing scheduling through the web.

A Framework for Understanding Cellular Manufacturing Systems

Many practical benefits, such as superior quality of products and short manufacturing lead times, are usually associated with Cellular Manufacturing. These and other benefits can lead to important competitive advantages f or companies. However, to fully achieve these benefits there is a need for an evolution from the traditional concept of CM to the more comprehensive one, which we call Product Oriented Manufacturing. Here, systems are dynamically reconfigured for the total manufacturing of complete products, not parts only.

Mechatronics education at the University of Minho: a summary of the present; perspectives for the future

The paper describes the topics on Mechatronics related subjects currently taught at the School of Engineering of Minho University and refers to the respective courses. The aims and syllabuses of undergraduate and postgraduate subjects, laboratory facilities and project topics are presented and discussed, together with a sequence of laboratory coursework aimed at improving the theoretical understanding of subjects and the development of practical skills. A general structure is proposed for a postgraduate course in Mechatronics to be taught in three blocks: the first two giving access to a diploma, the third being a laboratory project and dissertation leading to an M.Sc. degree.

Design of Product Oriented Manufacturing Systems

A Product Oriented Manufacturing System is designed for the manufacture of a product or a family of similar products. POM may be seen as a development of traditional Cellular Manufacturing and tends to involve more than one cell. A POMS may either be physically organized in a single place or be made of distributed manufacturing or servicing units, thus comprising a virtual system. To be efficient, the POMS design should identify design phases and point to the data, methods and tools that should be used to obtain good design solutions. In this paper, one such methodology is proposed, together with an analysis of the conceptual configuration of the cells that are the building blocks of POM systems.

Resource-oriented scheduling for real world manufacturing systems

Scheduling algorithms that achieve good or near optimal solutions and can efficiently adapt them to perturbations are, in most cases, preferable to those that achieve optimal ones but that cannot implement such an adaptation. In fact, in real world, where problems are essentially of dynamic and stochastic nature, these methods or algorithms are of very little use. This is the case with most algorithms for solving the so-called static scheduling problem for different setting of both single and multi-machine systems arrangements. This paper is concerned with a scheduling system, based on Genetic Algorithms, for the resolution of the dynamic version of the same problem. An additional constraint will be considered in our approach for the JSSP, the existence of different job release and due dates and different assembly levels for the jobs.

An XML Knowledge Base System for Scheduling Problems

Production Scheduling is an important function strongly contributing to the competitiveness of industrial and service companies. In this communication we make a contribution for XML based specification of scheduling concepts in order to allow for a standard representation of scheduling problems and related tasks. This information modeling is used in the development of a web based decision support system for the resolution of scheduling problems. An XML-based Knowledge Base System may be useful not only to facilitate the specification of scheduling problems but also in the search for the most suitable available algorithms and methods, which can then be used for finding good solutions to the problems. The existing algorithms, as well as their corresponding implementations, may either be local or remotely available, through the Internet.

A genetic algorithm for the dynamic single machine scheduling problem

This paper starts by studying the performance of two interrelated genetic algorithms (GA) for the static Single Machine Scheduling Problem (SMSP). One is a single start GA, the other, called MetaGA, is a multi-start version GA. The performance is evaluated for total weighted tardiness, on the basis of the quality of scheduling solutions obtained for a limit on computation time. Then, a scheduling system, based on Genetic Algorithms is proposed, for the resolution of the dynamic version of the same problem. The approach used adapts the resolution of the static problem to the dynamic one in which changes may occur continually. This takes into account dynamic occurrences in a system and adapts the current population to a new regenerated population

Developing a Web Scheduling System Based on XML Modeling

In manufacturing enterprises, it is important nowadays, as a competitive strategy, to explore and use software applications, now becoming available through the Internet and Intranets, for solving scheduling problems. This work gives a contribution for a better resolution process of scheduling problems, by means of web-based computation. An XML-based specification framework for scheduling is proposed. This specification provides a general model of scheduling problems and related tasks, and consequently a method of describing each particular problem and algorithm, by user information introduction. The main objective of this kind of specification is to make possible flexible communication among different scheduling applications, in a web-based scheduling decision support system.

An Inter-Machine Activity Coordination based Approach for Dynamic Job Shop Scheduling

The problem of finding good solutions to scheduling problems is very important to real manufacturing systems because the production rate and production costs are very dependent on the schedules used for controlling the flow of work through the system. Most research in scheduling focuses on optimisation of static and dynamic deterministic problems where all problem data are known before scheduling starts. However many real world optimisation problems are nondeterministic, in which changes may occur continually. This paper presents an approach for dynamic, nondeterministic job shop scheduling This approach starts with a scheduling framework, based on Genetic Algorithms for the resolution of the deterministic Job-Shop Scheduling Problem (JSSP), which considers job release times, job due dates and different assembly levels. This framework is based on a decomposition of the Job-Shop Scheduling Problem into a series of deterministic Single Machine Scheduling Problem (SMSP) and on a Genetic Algorithm (GA), which solves each SMSP whose solutions are, then, integrated. For this a coordination mechanism is proposed. Finally, the approach used adapts the resolution of the deterministic problem to the non-deterministic one in which changes may occur continually. This takes into account dynamic occurrences in a manufacturing system and adapts the current population to a new regenerated population.