Development of an Optimal Production Plan Using Fuzzy Logic Tools

2019 ◽  
pp. 211-218
Author(s):  
Maksim Kluchnikov ◽  
Elena Matrosova ◽  
Anna Tikhomirova ◽  
Svetlana Tikhomirova
Keyword(s):  
Fuzzy Logic ◽  
Production Plan ◽  
Optimal Production

scholarly journals Multiobjective Optimization Model of Production Planning in Cloud Manufacturing Based on TOPSIS Method with Combined Weights

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-15
Author(s):  
Zhiru Li ◽  
Wei Xu ◽  
Huibin Shi ◽  
Qingshan Zhang ◽  
Fengyi He
Keyword(s):  
Multiobjective Optimization ◽  
Production Planning ◽  
Mass Customization ◽  
Evaluation Model ◽  
Cloud Manufacturing ◽  
Production Plan ◽  
Topsis Method ◽  
Nsga Ii ◽  
Optimal Production ◽  
Planning Scheme

Combined with the research of mass customization and cloud manufacturing mode, this paper discussed the production planning of mass customization enterprises in the context of cloud manufacturing in detail, analyzed the attribute index of manufacturing resource combination, and given a system considering the characteristics of batch production in mass customization and the decentralization of manufacturing resources in cloud manufacturing environment. Then, a multiobjective optimization model has been constructed according to the product delivery date, product cost, and product quality that customers care most about. The Pareto solution set of production plan has been obtained by using NSGA-II algorithm. This paper established a six-tier attribute index system evaluation model for the optimization of production planning scheme set of mass customization enterprises in cloud manufacturing environment. The weight coefficients of attribute indexes were calculated by combining subjective and objective weights with analytic hierarchy process (AHP) and entropy weight method. Finally, the combined weights calculated were applied to the improved TOPSIS method, and the optimal production planning scheme has been obtained by ranking. This paper validated the effectiveness and feasibility of the multiobjective model and NSGA-II algorithm by the example of company A. The Pareto effective solution has been obtained by solving the model. Then the production plan set has been sorted synthetically according to the comprehensive evaluation model, and the optimal production plan has been obtained.

scholarly journals USING THE METHOD OF SEQUENTIAL RESTRICTIONS FOR SOLVING A DUAL-OBJECTIVE PROBLEM OF PRODUCTION PLANNING

2020 ◽  
Vol 11 (87) ◽  
Author(s):  
Nataliia Dovha ◽  
◽  
Hryhorii Tsehelyk ◽  
Keyword(s):  
Optimization Problem ◽  
Production Efficiency ◽  
Point Of View ◽  
Main Task ◽  
Production Plan ◽  
Optimal Production ◽  
Economic Point ◽  
Use Of Resources ◽  
Maximum Profit

The processes of optimization of the production plan according to certain criteria by modeling were investigated. Achieving effective results directly depends on the optimal production plan. The most important thing in determining the optimal production plan is the choice of modeling criteria. For the most part, the quality of decisions is characterized not by one but by many incomparable criteria. Therefore, it is necessary to make decisions based not on one but on many criteria. This so-called multi-objective optimization problem. For solving such problems is widely used mathematical methods. Mathematical approach can be used to solve problems in any particular activity as mathematics abstracted from specific features characteristic of a particular solution. Therefore, from the point of view of mathematics, the optimal result can be obtained with various established criteria, but from the economic point of view it is important to choose the ones that are of decisive importance. That is, their weight is important for the consumer when making a purchase decision, and for the manufacturer – in terms of production capabilities of certain types and results (production efficiency). The basis of the operation of any enterprise is a production program (production and sales plan). The main task of the production plan is to meet the needs of consumers in high-quality products, which are produced with the best use of resources, on the one hand, and the enterprise to get the maximum profit, on the other. With this in mind, a two-criteria optimization model that allows to make a production plan was proposed. The plan ensures that products are produced with the best use of available resources and at the same time ensures maximum quality of manufactured products and maximum profit from sales of these products. The solution of the problem with two objective functions and linear constraints is achieved by step-by-step solution of the proposed mathematical model of optimization of the production plan using the method of sequential restrictions. The simplex method was also used. An example shows an algorithm for solving the optimization problem.

scholarly journals PENENTUAN JUMLAH PRODUKSI SHAMPO DENGAN FUZZY INFERENCE SYSTEM SUGENO: STUDI KASUS PT. GUARDIAN PHARMATAMA TANGERANG

2017 ◽  
Vol 1 (2) ◽  
Author(s):  
Ri Sabti Septarini
Keyword(s):  
Fuzzy Logic ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Fuzzy Inference ◽  
Production Plan ◽  
Inference System ◽  
Fuzzy Variables ◽  
Fuzzy Input ◽  
A Company

ABSTRACTHuman are always faced with taking a decision. It also happens to a company in the process of determining which employees. In determination the production plan required a lot of considerations in case of taking decisions. Beside that, the number of employees in a company is to determine who get the production plan of the achievement. System is made to determine employees who will get benefits achievement based on the some criteria have been determined by the company. These criterias will be used as fuzzy input which also process a called fuzzy variables. In this research will construct decision support system by using fuzzy logic with fuzzy variables input that are productivity, quality tabbing and discipline. In of fuzzy logic method there are three stages, namely stage fuzzification, inference and deffuzification. At this stage of the fuzzy inference used the Sugeno method. The results of this experiments has performed that the system is able to display the production planning data for the calculation of the value of production that have been determined based on fuzzy logic with fuzzy variables. Keyword: Decision Support System, Fuzzy Logic,  Sugeno.

scholarly journals Scenario for applying the duality theory when planning production in the industry

E-Management ◽  
2020 ◽  
Vol 3 (3) ◽  
pp. 28-33
Author(s):  
A. T. Ershov ◽  
E. A. Gubareva ◽  
E. L. Nolde ◽  
M. V. Efimova
Keyword(s):  
Duality Theory ◽  
Production Management ◽  
Planning Problem ◽  
Problem Solution ◽  
Production Plan ◽  
Optimal Production ◽  
Scarce Resources ◽  
Planning Models ◽  
Total Profit ◽  
Production Company

The task of drawing up an optimal production plan for an enterprise with limited resources and problem solution of bridging production bottlenecks for only one enterprise are of limited interest. New technical capabilities due to the volume and speed of data transmission and processing, allow you to solve new problems in which the apparatus of the duality theory can be fully used.The authors consider the problem of planning the optimal production company (firm, industry, ministry) volume, which structurally has a certain coordinating (managing) center and a network of enterprises (branches), which can be located in different regions, and are not connected with each other. Each of the branches has its own technological matrix of resource costs for output, resource reserves, expected profit from the sale of each type of product unit.An iterative algorithm for finding production plans for each of the enterprises is proposed, when implementing which the total profit of the company can be increased. The Center finds the optimal production plan for each of the enterprises according to this algorithm and using the classical formula of the optimal production planning problem. Further, for each of them, the Center, solving the problem of resolving production bottlenecks for each of the enterprise, determines the supply volumes of resources scarce. The Center supplies scarce resources to enterprises and forms a new adjusted output plan for each of the enterprises. If it is impossible to supply scarce resources to meet the needs of all enterprises in the company, the options for the most promising planning models are offered, under which the total profit of all enterprises in the company will be the greatest.The implementation of the planning scenarios proposed below becomes real when switching to digital production management methods.

Production and maintenance strategies for parallel machines with load transfer in case of failure

2019 ◽  
Vol 25 (4) ◽  
pp. 525-544
Author(s):  
Jérémie Schutz ◽  
Anis Chelbi ◽  
Nidhal Rezg ◽  
Safa Ben Salem
Keyword(s):  
Production Rate ◽  
Failure Rate ◽  
Parallel Machines ◽  
Load Transfer ◽  
Production Costs ◽  
The Other ◽  
Random Time ◽  
Production Plan ◽  
Optimal Production ◽  
Content Type

PurposeThe purpose of this paper is to deal with the problem of integration of production and maintenance policies. In this context, the authors consider production systems made of parallel machines producing a single product over a finite horizon made of equal periods for which a forecasted demand is known. The authors investigate the impact of switching production in case of failure of any given machine.Design/methodology/approachA mathematical model is first developed to find an optimal production plan which minimizes the average total storage, shortage and production costs. Then, using this optimal production plan and taking into account the influence of the production rate on the degradation of each machine, optimal preventive maintenance (PM) policies are proposed for the situations with and without switching.FindingsOptimal production rates are determined for each production period and for each machine. Optimal PM periods are also computed for each machine.Practical implicationsUsually, in manufacturing systems, the production rate of a machine influences its failure rate. In case a machine fails, it takes a random time to repair it during which production is lost. The paper attempts to propose a switching policy (SP) according to which the lost production is compensated by all the other machines. The effects of the SP coupled with the PM strategy are shown through a numerical example.Originality/valueContrarily to previous works, the authors consider more realistic settings with a non-negligible random time for repairing failed machines. In order to compensate the lost production during the repair of a failed machine, a SP is proposed to transfer the load uniformly to all the other machines. As a result, those machines will produce at a higher production rate and will consequently have their failure rate increased. It will therefore be essential to determine an optimal PM schedule knowing that durations of these activities are not negligible. It is shown that the simultaneous implementation of periodic PM and load transfer in case of failure is the most economical integrated strategy.

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