F. Khaksar-Haghani, N. Javadian, R. Tavakkoli-Moghaddam , A. Baboli , R. Kia,
Volume 22, Issue 3 (9-2011)
Abstract
Dynamic cellular manufacturing systems, Mixed-integer non-linear programming, Production planning, Manufacturing attributes |
This paper presents a novel mixed-integer non-linear programming model for the design of a dynamic cellular manufacturing system (DCMS) based on production planning (PP) decisions and several manufacturing attributes. Such an integrated DCMS model with an extensive coverage of important design features has not been proposed yet and incorporates several manufacturing attributes including alternative process routings, operation sequence, processing time, production volume of parts, purchasing machine, duplicate machines, machine depot, machine capacity, lot splitting, material flow conservation equations, inflation coefficient, cell workload balancing, budget constraints for cell construction and machine procurement, varying number of formed cells, worker capacity, holding inventories and backorders, outsourcing part-operations, warehouse capacity, and cell reconfiguration. The objective of the integrated model is to minimize the total costs of cell construction, cell unemployment, machine overhead and machine processing, part-operations setup and production, outsourcing, backorders, inventory holding, material handling between system and warehouse, intra-cell and inter-cell movements, purchasing new machines, and machine relocation/installation/uninstallation. A comprehensive numerical example taken from the literature is solved by the Lingo software to illustrate the performance of the proposed model in handling the PP decisions and to investigate the incorporated manufacturing attributes in an integrated DCMS .
Hassan Rashidi, Fereshteh Azadi Parand,
Volume 30, Issue 3 (9-2019)
Abstract
One of the modern paradigms to develop a system is object oriented analysis and design. In this paradigm, there are several objects and each object plays some specific roles. There is a sequence of activities to develop an analysis model. In the first step, we work in developing an initial use case model. Then in the second step, they identify a number of concepts and build a glossary of participating objects. Identifying attributes of objects (and classes) is one of the most important steps in the object-oriented paradigm. This paper proposes a method to identify attributes of objects and verify them. The method is also concerned itself with classifying and eliminating the incorrect attributes of objects. Then the method is evaluated in a large application, a Control Command Police System. After that, several guidelines on attributes of objects, based on the practical experience obtained from the evaluation, are provided.
