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Showing 7 results for Subject: Manufacturing Process & Systems

Abbas Dideban, Maysam Zareiee, Ali A. Orouji, Hassan Rezaei Soleymanpour ,
Volume 24, Issue 1 (2-2013)
Abstract

This paper deals with the problem of forbidden states in discrete event systems modeled by Petri Net. To avoid the forbidden states, some constraints which are called Generalized Mutual Exclusion Constraints can be assigned to them. Enforcing these constraints on the system can be performed using control places. However, when the number of these constraints is large, a large number of control places must be connected to the system which complicates the model of controller. In this paper, the objective is to propose a general method for reducing the number of the mentioned constraints and consequently the number of control places. This method is based on mixing some constraints for obtaining a constraint verifying all of them which is performed using the optimization algorithms. The obtained controller after reducing the number of the control places is maximally permissive.
Hadi Mokhtari , Ashkan Mozdgir,
Volume 26, Issue 2 (7-2015)
Abstract

Assembly lines are special kinds of production systems which are of great importance in the industrial production of high quantity commodities. In many practical manufacturing systems, configuration of assembly lines is fixed and designing a new line may be incurred huge amount of costs and thereby it is not desirable for practitioners. When some changes related to market demand occur, it is worthwhile to re-balance an existing line rather than balancing a new one. Hence, in this paper we suggest a re-balancing model of an existing assembly line in which a new demand related cycle time (CT) is embedded to the traditional assembly line balancing problem (ALBP) as a new parameter. It does not focus on balancing a new line instead it considers a more realistic problem which is re-balancing an existing line. The objective is to re-schedule the tasks in order to reduce the current CT to the new required one such that two criteria are optimized: (i) minimization of the incurred costs and (ii) minimization of non-smoothing of reconfigured line. To solve the considered problem, an effective differential evolution algorithm is developed. Furthermore, to enhance the performance of algorithm, its parameters are optimized by the use of Taguchi method which is a conventional statistical technique for parameter design. The obtained results from computational experiments on benchmark instances show the effectiveness of suggested algorithm against other methods.

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Rassoul Noorossana, M. Nikoo,
Volume 26, Issue 2 (7-2015)
Abstract

In many manufacturing processes, the quality of a product is characterized by a non-linear relationship between a dependent variable and one or more independent variables. Using nonlinear regression for monitoring nonlinear profiles have been proposed in the literature of profile monitoring which is faced with two problems 1) the distribution of regression coefficients in small samples is unknown and 2) with the increasing complexity of process, regression parameters will increase and thereby the efficiency of control charts decreases. In this paper, wavelet transform is used in Phase II for monitoring nonlinear profiles. In wavelets transform, two parameters specify the smoothing level, the first one is threshold and the second one is decomposition level of regression function form. First, using the adjusted coefficient of determination, decomposition level is specified and then process performance is monitored using the mean of wavelet coefficients and profile variance. The efficiency of the proposed control charts based on the average run length (ARL) criterion for real data is compared with the existing control charts for monitoring nonlinear profiles in Phase II

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Javad Rezaeian, Masoud Shafipour,
Volume 28, Issue 3 (9-2017)
Abstract

This research deals with a hybrid flow shop scheduling problem with parallel batching, machine eligibility, unrelated parallel machine, and different release dates to minimize the sum of the total weighted earliness and tardiness (ET) penalties. In parallel batching situation, it is supposed that number of machine in some stages are able to perform a certain number of jobs simultaneously. Firstly, with respect to the proposed problem a mixed integer linear programming model is developed. Since the problem is NP-hard, for solving large size problems, a hybrid meta-heuristic algorithm which combines artificial immune system and simulated annealing is proposed. The performance of hybrid algorithm is tested by some numerical experiments and the results show its superiority to the other two algorithms.


Bardia Behnia, Iraj Mahdavi, Babak Shirazi, Mohammad Mahdi Paydar,
Volume 28, Issue 3 (9-2017)
Abstract

Nowadays, the necessity of manufacturers’ response to their customers’ needs and their fields of activities have extended widely. The cellular manufacturing systems have adopted reduced costs from mass-production systems and high flexibility from job-shop manufacturing systems, and therefore, they are very popular in modern manufacturing environments. Manufacturing systems, in addition to proper machinery and equipment, workforces and their performance play a critical role.

Staff creativity is an important factor in product development, and their interest in cooperating with each other in the work environment can help the growth and maturity of this factor. In this research, two important aspects of cellular manufacturing take into consideration: Cell formation and workforce planning. Cell formation is a strategic decision, and workforce planning is a tactical decision. Practically, these two sectors cannot be planned simultaneously, and decision making in this regard is decentralized. For this reason, a bi-level mathematical model is proposed. The first level aims to reduce the number of voids and exceptional elements, and the second level tends to promote the sense of interest between the workforces for working together, which will result in synergy and growth of the organization.


Bahman Esmailnezhad, Mohammad Saidi-Mehrabad,
Volume 29, Issue 1 (3-2018)
Abstract

This paper deals the stochastic cell formation problem (SCFP). The paper presents a new nonlinear integer programming model for the SCFP in which the effect of buffer size on the grouping efficacy of cells has been investigated. The objective function is the maximization of the grouping efficacy of cells. A chance constraint is applied to explore the effect of buffer on the SCFP. Processing time and arrival time of the part for each cell are considered stochastic and are following exponential probability distribution. To find out the optimal solution in a reasonable time, a heuristic approach is used to linearize the proposed nonlinear model. This problem has been known as an NP-hard problem. Therefore, two metaheuristic methods, namely; genetic algorithm and particle swarm optimization are employed to solve examples. The parameters of the algorithms are calibrated using Taguchi and full factorial methods, and the performances of the algorithms on the examples of various sizes are analyzed against global solutions obtained from Lingo software’s branch and bound (B&B) in terms of quality of solutions and computational time.
Mangesh Phate, Shraddha Toney, Vikas Phate,
Volume 30, Issue 1 (3-2019)
Abstract

In the Wire EDM of oil hardening die steel materials is a complicated machining process. Hence to find out the best set of process parameters is an important step in wire EDM process. Multi-response optimization of machining parameters was done by using analysis called desirability function analysis coupled with the dimensional analysis approach. In the present work, based on Taguchi’s L27 orthogonal array, number experiments were conducted for OHNS material. The WEDM process parameters such as, pulse on time , pulse off time, input current, wire feed rate and the servo voltage are optimized by multi-response considerations such as material removal rate and surface roughness. Based on desirability analysis, the most favorable levels of parameters have been known. The significant contribution of parameters is determined by dimensional analysis. The experimental results show that the results obtain by using DA approach has a good agreement with the measured responses. The correlation up to  99% has been achieved between the developed model and the measured responses by using dimensional analysis approach. 
In the Wire EDM of oil hardening die steel materials is a complicated machining process. Hence to find out the best set of process parameters is an important step in the wire EDM process. Multi-response optimization of machining parameters was done by using analysis called desirability function analysis coupled with the dimensional analysis approach. In the present work, based on Taguchi’s L27 orthogonal array, number experiments were conducted for OHNS material. The WEDM process parameters such as pulse on time, pulse off time, input current, wire feed rate, and the servo voltage are optimized by multi-response considerations such as material removal rate and surface roughness. Based on desirability analysis, the most favorable levels of parameters have been known. The significant contribution of parameters is determined by dimensional analysis. The experimental results show that the results obtain by using DA approach has a good agreement with the measured responses. The correlation up to  99% has been achieved between the developed model and the measured responses by using dimensional analysis approach. 

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