production planning
fahimeh tanhaie
Abstract
Mixed-model assembly is a particular set of production lines assembling a family of product models with similar specifications. Designing paced assembly lines faces two primary problems: balancing and sequencing. The balancing quality is closely associated with the described production sequence. Although ...
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Mixed-model assembly is a particular set of production lines assembling a family of product models with similar specifications. Designing paced assembly lines faces two primary problems: balancing and sequencing. The balancing quality is closely associated with the described production sequence. Although these two are problems of one assembly method, they do not occur simultaneously; balancing poses a problem during the line designing, whereas sequencing becomes problematic at the fluctuating demand of markets. The present research presents a balancing and sequencing problem and the proper times to set up the machines between tasks. Unlike a majority of published studies, this paper contains two successive tasks' setup times in dynamic periods, in which periods also impact the flowing period. A mathematical is described with a number of objective functions, reducing the inappropriate assembly line sequence, reducing setup cost, and reducing the inappropriate product balance and the impact of this situation on incomplete tasks. Thus, the literature has presented several metaheuristic algorithms to solve the problems nearly optimally. This study uses a multi-objective particle swarm optimization algorithm, a suitable approach, to create models and solutions. Various problems are designed in different sizes and compared, and the decision variable sensitivity is investigated to prepare managerial intuitions. The findings propose that the presented algorithm can solve the research problems more efficiently.
production planning
Ommolbanin Yousefi; Saeed Rezaeei Moghadam; Neda Hajheidari
Abstract
One of the most important decisions taken in a supply chain is the issue of aggregate production planning where a program-within a medium time-range-- is determined for optimum manufacturing of all products using shared equipment and resources. This research presents a multi-objective model that helps ...
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One of the most important decisions taken in a supply chain is the issue of aggregate production planning where a program-within a medium time-range-- is determined for optimum manufacturing of all products using shared equipment and resources. This research presents a multi-objective model that helps the decision makers to make such decisions. The proposed model comprises four main objectives, the first one of which considers minimizing costs (including costs of manufacturing product, supplying, maintenance, inventory stock shortage, and expenditures related to man power). The second objective is defined as maximizing customers’ satisfaction. Minimizing suppliers’ satisfaction makes up the third objective and maximizing the quality of the manufactured products constitutes the fourth objective. In this model, the demand parameter is investigated under uncertain conditions; hence, other parameters influenced by this parameter are also presented under uncertain conditions occurring within three differing scenarios. This model is solved through LP- metric and the LINGO v14.0.1.55 software. At first the model is solved by means of numerical example; then it is solved by the actual data that are related to a military industry. Finally, process, variables like inventory level, overtime work hours etc, are valued with the help of closed-loop supply chain of the proposed model.
