International Journal of Industrial Engineering: Theory, Applications and Practice
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An Aggregate Production Planning Strategy Selection Methodology based on Linear Physical Programming
Get PDFIn this paper, a multi-objective model for aggregate production planning is presented which includes two objectives: (1) minimized cost and (2) minimized effect on the workforce motivation level caused by hire/layoff decisions. Then, six strategies are considered and the most appropriate one is determined to structure the plan. These strategies are set the regular time production quantities in a certain value which is unique for each. A preference based optimization method called Linear Physical Programming (LPP) is used to solve the model. A forecasting phase which chooses the convenient method to forecast the demand for planning horizon is embedded to study in addition to application of LPP to an APP model as another key contribution of this paper
EXTRACTION OF ELECTRICAL TEST PARAMETERS BY ARTIFICIAL NEURAL NETWORK
No full textIn semiconductor industry, cycle time of the wafer fabrication is very crucial and one of the contributing factors comes from wafer testing. This paper presents the application of back propagation Artificial Neural Network (ANN) model designed to infer electrical test parameters from the given list of parameters with the intention of reducing test time, to enhance throughput, and to improve cycle time. It also investigates if the ANN based inference system can be established as a robust method for parameter extraction to provide an accurate electrical value to minimize false measurement. It is shown that the ANN model does quite an excellent job and the predicted values are in good agreement with the measured value
ANALYZING THE IMPACT OF SPACE UTILIZATION AND PRODUCTION PLANNING ON PLANT SPACE REQUIREMENTS - A CASE STUDY AND METHODOLOGY
No full textIn 2001, the authors took part in a study aimed at eval uating the costs and benefits of centralizing warehousing activities for a network of four plants at a fi rst-tier automotive suppl ier. A key issue raised during the study centered on how much space was available at each of the plants, and how much space could be recaptured through improved layout and space utilization efforts, and through improved production planning practices. This paper focuses on the steps carried out to 1) quantify the space at each plant, 2) estimate manufacturing, inventory storage, and shipping and receiving space utilization levels, and 3) estimate the impact of production planning on inventory space requirements
OPTIMAL PRICING AND GUARANTEED LEAD TIME WITH CONSIDERATION OF LATENESS PENALTIES
No full textThis paper studies the price and guaranteed lead time decision of a supplier that offers a fixed guaranteed lead time for a product. If the supplier is not able to meet the guaranteed lead time, the supplier must pay a lateness penalty to customers. Thus, the expected demand is a function of the price, guaranteed lead time and lateness penalty. We first develop a mathematical model for a given supply capacity to determine the optimal price, guaranteed lead time and lateness penalty to maximize the total profit. We then consider the case where it is also possible for the supplier to increase capacity and compute the optimal capacity
PERFORMANCE MODELING AND ANALYSIS OF A COMPLEX REPAIRABLE INDUSTRIAL SYSTEM
No full textHigh reliability and availability are the supreme importance of a complex electromechanical system. The imprecise, uncertain, and often inaccurate data collection, uncertainty, and ambiguity have been inevitably associated with a complex industrial system. The Markov approach has proven to be a unified tool to evaluate the reliability of a complex industrial system. In the present research, the author presented a structured and methodological technique to analyze the reliability and availability of various subsystems of coal crushing unit of a thermal power plant using the traditional Markov birth-death process and demonstrated it using a probabilistic approach. The approach consists of breaking up the coal crushing unit/system into various subsystems with three feasible states labeled in the transition diagram. Then using the Markov approach, a probabilistic stochastic model has been developed using Chapman–Kolmogorov equations. The results of the studies are of utmost importance for the plant management in order to take timely decisions for maintaining the system in the upstate for a long duration and take corrective maintenance action
A TEST OF FIT FOR LINDLEY DISTRIBUTION
No full textIt is important to develop efficient goodness of fit test for Lindley distribution because it is one of the fundamental models applied for reliability models. This article introduces some test statistics for examining the Lindley goodness of fit based on the empirical distribution function. Critical points and the power of the tests are obtained by Monte Carlo simulation. We show that the proposed tests have a good performance against different alternatives, and therefore, these tests can be confidently used in practice. Finally, the proposed tests are illustrated by a real data example
CLUSTER-BASED PRIORITY LIST GENERATION FOR RESOURCE-CONSTRAINED PROJECT SCHEDULING PROBLEMS
Get PDFConstructive Heuristics for the Resource Constraint Project Scheduling Problems (RCPSP) are preferred scheduling methods when the project network broadens. Then, to generate a good schedule from these heuristics, the priority list used in the algorithm becomes crucial. This paper proposes a Cluster-Based Priority List (CB-PL) method for generating lists to improve makespans of schedules obtained from constructive heuristics. The method creates more intellectual priority lists that generate lower makespans. The approach is built and fine-tuned upon the existing relative literature. The performance of the method is measured by comparing the makespan results. The experiment for the comparison uses serial and parallel scheduling schemes with seven priority rules. Then the experiment is tested through a set of benchmark data. Finally, schedules obtained through the CB-PL showed significant makespan reductions and increases in an overall number of better solutions
MATHEMATICAL MODELING FOR THE SIMULTANEOUS ALLOCATION AND SCHEDULING OF TOUR GUIDES: A PRACTICAL PROBLEM IN WAR TOURISM
No full textThis study is a preliminary quantitative (mathematical) research conducted in war tourism. The study aims to minimize the planning, allocation, and scheduling time of "Rahian-e Noor" narrators and minimize the number of narrators. Another critical issue is to consider their preferences and competencies. The point of this study is that human capital (narrators) operates "voluntarily" without receiving any payment. Therefore, firstly, the issue of minimizing the costs of allocating salaries and benefits to human capital is ruled out. Second, some considerations must be considered in formulating constraints, including providing the narrators with sufficient rest times and, as far as possible, not forcing them to perform the tasks assigned. This study modeled a set of different constraints in a four-objective mathematical problem. This model was solved in several sample problems using two new metaheuristic algorithms, i.e., the crow search algorithm (CSA) and gray wolf optimizer (GWO). The comparison results of these two methods showed the superiority of the CSA over the GWO. Finally, a case study was conducted comparing the model output with the current situation of tour guides’ allocation, which indicated a significant improvement in different objectives
MANAGING PRODUCTION PROCESS IN A PET RESIN INDUSTRY USING DATA MINING AND GENETIC PROGRAMMING
No full textBalancing the production volume and costs because of the petrol prices and, thus, supply change rapidly is one of the managerial issues in the polymer industry. In this study, data about the chemical operation of PET resin products have been used, and monthly and annual production plans and their influencing factors have been analyzed with data mining techniques in the plastic industry. The algorithm of find-dependencies used to find effective parameters has been identified in the levels of monthly production, sale, and end-of-the-month inventory. Rules have been established with the find-laws algorithm, and genetic programming is used to predict the outputs. It shows that high-accuracy applicable rules can be obtained with these technics. The rules proved to be more accurate at the end of the comparison and became employable for decision-support to the production process of the PET Resin factory. With these techniques used for the first time on such a problem in the literature, all similar companies can provide clarity in their strategic decisions and efficiency in using company resources and production
ONLINE PARAMETERS ESTIMATION OF TIME-DELAYED DYNAMICS OF PROCESSES FOR INDUSTRIAL USE
No full textThis article presents an online identification scheme for modeling time-delayed processes using a simple setpoint-weighted relay autotuning approach for industrial use. Four sets of mathematical expressions are prescribed for the identification of process dynamics using the limit cycle information in terms of two second-order plus time delay and two first-order plus time delay models. The model parameters are directly identified from the explicit expressions derived based on setpoint weighted relay gain, proportional-integral-derivative (PID) controller parameters, and closed-loop marginal criteria. An experimental setup of a single-input-single-output (SISO) liquid level control system is considered to validate the proposed identification scheme. Two first-order plus time delay transfer functions are identified from the proposed online method for the considered system and compared with a model obtained from an offline method