Integrating discrete-event simulation into production systems design and operation.

摘要

Success of a production system is tied to its ability to recondition itself as the market demand, technology, and competition change dynamically, which requires integration of knowledge, experience and forecasting into the production systems operation via discrete event modeling. The effort provided in this research develops and proposes tools and techniques that address product development, production systems design and operation related challenges while emphasizing the planning and scheduling components.;The product aspect of the effort focuses on product and product family design and development, in which Product Cost Scoring (PCS) is developed to assign profit-based scores to the members of a product family. The production systems development and operation aspect of the effort focuses on integration of decision-making, planning, and scheduling into a single platform. The decision-making component of the production systems development addresses the challenge of weight assessment via Hierarchical Weight Assessment (HWA) technique. Planning and scheduling of production systems is closely tied to supply chain management, in which the value of the products and processes are connected. The value of the supply chain can be increased by maximizing the value and minimizing the wastes of the products and processes involved in that supply chain, both of which can be achieved by proper scheduling. Several case studies are examined throughout this dissertation in an effort to demonstrate the effectiveness of the proposed tools and techniques. These case studies focus on product, product family, and production operation as they demonstrate the implementation of these tools and techniques.;The techniques and case studies provided and examined in this dissertation procures the development of production systems design and operation in an integrated decision-based environment, which is supported by discrete-event modeling and simulation. The tools and techniques provided in this dissertation can be implemented to variety of case studies individually to address specific challenges or integrated to address production process operational challenges.