Beschreibung
This book addresses an integrated process planning and scheduling problem where the objective is to improve system efficiency and enhance resource utilization, thereby ameliorating the production activities. The notion of simultaneous manufacturing of prismatic parts has been conceived in this work to improve the system output in both cost and time frame. The computational prowess of DNA algorithm in preliminary graph based combinatorial optimization has been utilized to resolve the complexities of the proposed Integrated Process Planning and Scheduling (IPPS) framework. Further, the inherently parallel search strategy and structured architecture used in DNA algorithm meets the implementation requirements of IPPS. Being first of its kind attempt, the proposed strategy has first been tested over standard test functions, thus establishing its superiority in numerical optimization. Thereafter, its application to four integrated process planning and scheduling problems (three benchmarks and one simulated) with real sized data authenticate the robustness of the proposed solution methodology.
Autorenporträt
Manish Bachlaus is working with Inductis , India as Assistant Manager in Data Analytics. He received his M.S. degree in Advanced Manufacturing and Enterprise Engineering from University of Texas at San Antonio, USA. His research interest includes Statistical modeling of manufacturing systems and Artificial Intelligence tools.
