Dynamic scheduling for complex engineer-to-order products (original) (raw)

Scheduling: New trends in industrial environment

Annual Reviews in Control, 2007

A major goal of a supply chain is to ''improve the flow of material between suppliers and customers at the highest speed''. This goal suggests making real time and global management decisions, which involves scheduling. In this paper, we briefly remind the evolution of scheduling activities in industrial environment, describe the current situation and emphasize the problems that call for solutions. #

Scheduling problems — An overview

Journal of Systems Science and Systems Engineering, 2003

There seems to be a significant gap between the theoretical and the practical aspects of scheduling problems in the job shop environment. Theoretically, scheduling systems are designed on the basis of an optimum approach to the scheduling model. However in the practice, the optimum that is built into the scheduling applications seems to face some challenges when dealing with the dynamic character of a scheduling system, for instance machine breakdown or change of orders. Scheduling systems have become quite complex in the past few years. Competitive business environments and shorter product life cycles are the imminent challenges being faced by many companies these days. These challenges push companies to anticipate a demand driven supply chain in their business environment. A demand-driven supply chain incorporates the customer view into the supply chain processes. As a consequence of this, scheduling as a core process of the demand-driven supply chain must also reflect the customer view. In addition, other approaches to solving scheduling problems, for instance approaches based on human factors, prefer the scheduling system to be more flexible in both design and implementation. After discussion of these factors, the authors propose the integration of a different set of criteria for the development of scheduling systems which not only appears to have a better flexibility but also increased customer-focus.

Planning and re-planning in project and production scheduling

Omega, 2002

Scheduling is a time and labor-intensive task. In addition, problems arise due to the lag time between the publication of the schedule and the start of the scheduled work period. During this time, conditions in the dynamic environment can, and often do, change (equipment breaks, orders are cancelled or increased, work force levels do not meet expectations, or a task simply takes longer than planned, for example). While the scheduling literature is broad, very little of it addresses re-planning and rescheduling. This research explores the use of tabu search (TS) seeded with a robust initial solution to determine "good" solutions for a posted schedule. It considers preemptive tasking priorities. The procedure then adapts the TS to focus on generating re-planning and rescheduling options in a project or production setting. The TS procedure was implemented in Java to be portable and to make the objects available for reuse and adaptation elsewhere in the planning hierarchy. Published by Elsevier Science Ltd.

A product oriented approach to Dynamic Scheduling

Proceedings of the IEEE International Conference on Industrial Technology, 2006

The purpose of this paper is to present a System scheduling, the results are much better when compared with for Dynamic Scheduling of Manufacturing Orders using a those obtained from other conventional methodologies. product Oriented approach, to be used in an integrated manner In this work a System for Dynamic Scheduling of for dynamic, interactive and iterative scheduling under a Manufacturing Orders is presented, to be used in an Scheduling Decision Support System. Here is described a due. .. ' date based scheduling method, where al the operations of one itredu mnner f S dyna ierctive and iteratIv task are scheduled before the next task is considered, a task is scheduling under a Scheduling Decision Support System. In considered to be the set of all the operations needed to produce the interactive scheduling first the system builds a schedule one product. and displays it in a Gantt chart [8]. After, the user may try to The referred method is to be applied to solve real world improve the schedule without breaking inviolable scheduling dynamic scheduling problems in a multi-order multi-resource constraints. For this the user may select from several choices environment, where the products to be processed have release modifying the chart by moving around the jobs or orders on times and due dates, and the resources are available in a limited the screen. Then, a rebuild-algorithm reschedules activities amount. Some realistic constraints are considered, such as that follow these manual changes. The interaction between multilevel tasks, shared resources, alternative resources and temporal constraints. The objective is to meet the deadlines for hualadsy all the tasks. Yet there is one limitation, pre-emption is not evolves allowed. II. PRODUCT ORIENTED APPROACH

A Review for Dynamic Scheduling in Manufacturing By Khalid Muhamadin

2018

This paper discusses review of literature of dynamic scheduling in manufacturing. First, the problem is defined. The scheduling problems are classified based on the nature of the shop configuration into five classes, i.e., single machine, parallel machines, flow shop, job shop, and open shop. A variety of approaches have been developed to solve the problem of dynamic scheduling. Dynamic scheduling could be classified into four categories, completely reactive scheduling, predictive-reactive scheduling, robust predictive reactive scheduling, and robust proactive scheduling. It is better to combine together different techniques such as operational research and artificial intelligence to overcome dynamic scheduling problems so as to endow the scheduling system with the required flexibility and robustness, and to suggest various orientations for further work is this area of research.

A survey of dynamic scheduling in manufacturing systems

Journal of Scheduling, 2009

In most real-world environments, scheduling is an ongoing reactive process where the presence of a variety of unexpected disruptions is usually inevitable, and continually forces reconsideration and revision of pre-established schedules. Many of the approaches developed to solve the problem of static scheduling are often impractical in real-world environments, and the near-optimal schedules with respect to the estimated data may become obsolete when they are released to the shop floor. This paper outlines the limitations of the static approaches to scheduling in the presence of realtime information and presents a number of issues that have come up in recent years on dynamic scheduling.

A review for Dynamic Scheduling in Manufacturing

— This paper discusses review of literature of dynamic scheduling in manufacturing. First, the problem is defined. The scheduling problems are classified based on the nature of the shop configuration into five classes, i.e., single machine, parallel machines, flow shop, job shop, and open shop. A variety of approaches have been developed to solve the problem of dynamic scheduling. Dynamic scheduling could be classified into four categories, completely reactive scheduling, predictive-reactive scheduling, robust predictive-reactive scheduling, and robust pro-active scheduling. It is better to combine together different techniques such as operational research and artificial intelligence to overcome dynamic scheduling problems so as to endow the scheduling system with the required flexibility and robustness, and to suggest various orientations for further work is this area of research.

Design of Scheduling Algorithms

Behavioral Operations in Planning and Scheduling, 2010

The academic field of production research has been growing rapidly over the last decades with researchers proposing numerous analytical and heuristic optimization methodologies for the solution of planning & scheduling problems. However, adaption by manufacturing companies is lagging behind. This paper suggests that the basic reason behind this imbalance is the inadequate representation of the planning & scheduling process when designing decision support systems. Hence, the algorithms that are designed and included in these systems might not reflect the problems that actually have to be solved in practice. In this paper we discuss the basic factors that are important for the development of planning & scheduling decision support systems. These factors will be based on insights from cognitive psychology, computer science, and operations management.