Title

A Study Of The Impact Of Production Scheduling Using Enterprise Simulation

Keywords

Enterprise simulation; Hybrid simulation; Scheduling; System dynamics

Abstract

The strong tendency toward integrated systems and the system thinking approaches are shaping the way manufacturing enterprises are being managed, especially in an environment of market globalization, ever varying customer requirements and increasing competition. To achieve a competitive advantage an enterprise must cope with these changes in the working environment. The future development of manufacturing simulation systems is directed to integrated enterprise modeling in two direction: horizontally by integration of manufacturing processes with the entire enterprise logistics chain, and vertically by integration of the decision making processes at strategic, tactical and operation levels [1]. In this work, we introduce a hybrid approach to the integration of discrete-event models with system dynamic models to simulate the entire manufacturing enterprise. This approach basically covers the strategic, tactical, and operational levels of decision-making in a single simulation of multiple models at different levels and resolutions. System dynamics (SD) is utilized to model the higher levels of decision-making in the enterprise. On the other hand, discrete-event simulation (DES) models are utilized for the factory and shop floor levels. Studying the interaction between strategic planning and the production activities is the core of this work. Discrete event simulation has been the most usable simulation tool in manufacturing systems. It has the ability to describe the most complex systems at any level of details while allowing tracking the status of individual entities and resources and estimate numerous performance measures associated with these entities various operating conditions. This makes it most appropriate approach to simulate the detailed production activities. At the higher levels of decisions making, the detailed approach of DES is not appropriate [2,3,4]. For one reason the decision maker at such levels do not prefer detailed analyses. In additions unlike manufacturing tasks data, the nonmanufacturing tasks data are only available as rough expert estimates [5]. For that we consider SD simulation, which is a system thinking approach that focuses on the structure of the system and its dynamic behavior due to taken management policies. Its central concept is that all the components of a system interact through causal relationships that come about through feedback loops. Thus a model is a dynamic picture of the perceived cause-and-effect relationship among system components. It can incorporate qualitative systems parameters as well. These features make SD well appropriate for simulating strategic and tactical decision making levels. It is understandable that the driving force for a company' strategic planning is its need and desire to manufacture competitive products. Operational scheduling on the other hand refers to the short-term decision problems in executing the company's business strategies and achieving the planned goals. Traditionally planning and scheduling used to be very distinct phases. Such distinction does not match the requirements of the current operating environments. However a practical holistic approach to coordinate and integrate them is not yet available. We consider a semiconductor enterprise, which typically works in a very dynamic and capital intensive industry. Top management decides based on market analysis to introduce a new generation of chips or enter a new electronics market. Scheduling receives a set of orders and designed goals with predefined release dates for the raw materials and due dates for finished products. Given the time consuming processes involved in semiconductor manufacturingoperations, scheduling is a complicated task that would involve the design of new processes that should consider the cost constraints of the management. Related strategic resources allocation decisions made at the enterprise levels are to be implemented at the production level have strong impact on the effectiveness of the scheduling and other production functions. Reciprocally the effectiveness, in executing top management plans to supply the required demand and in using the allocated resources, at the operational and tactical levels has direct impact on the ability of the enterprise to satisfy its market commitments and on its financial performance as well. Further when more than production plants exist within the enterprise (which is the case for a wide range of current manufacturing enterprises) the situation becomes more complicated especially when different the plants work at different levels of performance and different impacts and contributions to the enterprise's profitability. Planning, marketing and customer relations management functions at the strategic levels must be in close coordination with the shop floor level functions. Real time data reflecting the shop floor status must be available during the review of the business strategies and during deciding on introducing new products or entering new markets as well as during making the resources allocation decisions. These decisions must be made fast enough to seize available market opportunities which are always the target of many competitors. This proposed hybrid simulation environment provides the practical framework to achieve the needed integration. It is utilized to study the impact of the top decisions in developing a production schedule as well as in rescheduling the production facility as needed. Equivalently this hybrid simulation approach also allows for studying and the impact of the execution of that production schedules on the development of the objectives and possibly the strategies of the enterprise.

Publication Date

12-1-2004

Publication Title

IIE Annual Conference and Exhibition 2004

Number of Pages

839-840

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

Socpus ID

30144436295 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/30144436295

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