PRODUCTION AND OPERATIONS MANAGEMENT
Year:2013 | Volume:4 | Issue:1 (6)|Papers Count:8

The purpose of preventive maintenance management is to perform a series of tasks that prevent or minimize production breakdowns and improve reliability of production facilities. An important objective of preventive maintenance management is to minimize downtime of production facilities. In order to accomplish this objective, personnel should efficiently allocate resources and determine an effective maintenance schedule. Gopalakrishnan (1997) developed a mathematical model and four heuristic approaches to solve the preventive maintenance scheduling problem of assigning skilled personnel to work with tasks that require a set of corresponding skills. However, there are several limitations in the prior work in this area of research. The craft combination problem has not been solved because the craft combination is assumed as given. The craft combination problem concerns the computation of all combinations of assigning multi skilled workers to accomplishment of a particular task. In fact, determining craft combinations is difficult because of the exponential number of craft combinations that are possible. This research provides a heuristic approach for determining the craft combination and four new heuristic approach solution for the preventive maintenance scheduling problem with multi skilled workforce constraints. In order to examine the new heuristic approach and to compare the new heuristic approach with heuristic approach of Gopalakrishnan (1997), 81 standard problems have been generated based on the criterion suggested by from Gopalakrishnan (1997). The average solution quality (SQ) of the new heuristic approaches is 1.86% and in old heuristic approaches is 8.32%. The solution time of new heuristic approaches are shorter than old heuristic approaches. The solution time of new heuristic approaches is 0.78 second and old heuristic approaches is 6.43 second, but the solution time of mathematical model provided by Gopalakrishnan (1997) is 152 second.

In this article, the continuous-review inventory control system has been studied. A new constraint of demand dependent on the average percent of product shortage has been added to the problem. It means that the average demand has a direct relationship with shortage in a period. This constraint, which is related to the costs of credit loss of the organization due to product shortage, has been considered in the inventory model. In this paper, the mathematical model of this problem has been presented and then, two heuristic approaches based on the genetic and simulated annealing algorithms are developed. Computational results indicate that the simulated annealing algorithm can provide better results compare to the genetic algorithm.

In this paper, two different sub-problems are considered to solve a resource constrained project scheduling problem (RCPSP), namely i) assignment of modes to tasks and ii) scheduling of these tasks in order to minimize the make span of the project. The modified electromagnetism-like algorithm deals with the first problem to create an assignment of modes to activities. This list is used to generate a project schedule. When a new assignment is made, it is necessary to fix all mode dependent requirements of the project activities and to generate a random schedule with the serial SGS method. A local search will optimize the sequence of the activities. Also in this paper, a new penalty function has been proposed for solutions which are infeasible with respect to non-renewable resources. Performance of the proposed algorithm has been compared with the best algorithms published so far on the basis of CPU time and number of generated schedules stopping criteria. Reported results indicate excellent performance of the algorithm.

In this paper, a new robust model of multi-period portfolio problem has been developed. One of the key concerns in any asset allocation problem is how to cope with uncertainty about future returns. There are some approaches in the literature for this purpose including stochastic programming and robust optimization. Applying these techniques to multi-period portfolio problem may increase the problem size in a way that the resulting model is intractable. In this paper, a novel approach has been proposed to formulate multi-period portfolio problem as an uncertain linear program assuming that asset return follows the single-index factor model. Robust optimization technique has been also used to solve the problem. In order to evaluate the performance of the proposed model, a numerical example has been applied using simulated data.

Determination of optimal production lot size has been always noticed by researchers and various models have been proposed in this area. Among the subjects, which has been less considered in these models is machine failure. Obviously, a machine may encounter random failures during its working period and this makes clear the need for applying an appropriate maintenance policy for the machinery. In this paper based on assumptions such as authorized shortage, work in process inventory and possibility of producing defective products with and without the ability to re-work, EPQ model has been investigated and developed to select Preventive Maintenance (PM) policy for the machinery. In addition, by minimizing system’s total cost over a period of time, a formula has been presented for determining optimal production lot size and its application has been examined using various numerical examples.

The objective of this paper is to study organizational excellence based on Peters and Waterman model in Engineering Company of Isfahan Ghaem Sepahan. Eight variables have been evaluated in this model including bias for action; close to the customer; autonomy and entrepreneurship; productivity through people; hands-on, value-driven; stick to the knitting; simple form, lean staff; and simultaneous loose-tight properties. This research is typically descriptive and practical. Statistical population includes employees of Engineering Company of Isfahan Ghaem Sepahan. The sample size is 89 and is selected through random sampling method. Data has been collected by means of researcher self-made questionnaire with 45 questions and Likert’s five point scale. One variable t-test, T2 Hotelling and multi-variable variance analysis have been used for statistical analysis. Results reveal that the observed t is higher than the average level regarding Peters and Waterman organizational excellence variables. As a result, this company is an excellent organization based on the model. Finally, based on the studied model, a systematic approach has been developed.

In recent years, managing the interface between design and other activities has received considerable attention. Effective coordination among these areas is therefore vital for effectiveness of the organization. The ideal situation would be continuous interdepartmental contact with well-developed channels of communication. In this study, the best strategy for product design department has been chosen using the strategic formulation framework with fuzzy approach. Subsequently, alignment of each functional design strategy with SAPCO business strategies has been explained. Findings indicate that developing partnerships with global automotive and engineering design companies and building strategic alliances with rival firms to achieve competitive advantages have maximum alignment with business strategies. In addition, findings provide a basis for firms in evaluating the concurrent design strategies and a reference for them to strengthen their concurrent capabilities. There are few reports on sustained use of concurrent design as an on-going strategic process in an organization. This study aims at contributing to the concurrent design solutions.

One of the problems of today's banking system is overdue loans. The basic strategy for solving this problem is creating a credit rating system of customers. Financial ratios extracted from financial statements of companies have long been considered as one of the useful tools used for evaluating companies by individuals to predict future conditions. Therefore, in this study, ranking of companies in each industry has been discussed using Data Envelopment Analysis (DEA) and a number of inputs and outputs such as financial ratios and other important characteristics from the viewpoint of professors and credit experts. Then, ratings of the inputs and outputs (credit criteria) have been identified to distinguish and compare the types of industries using sensitivity analysis. Finally, the values of inputs and outputs have been studied for different industries. The research approach can be used by banks in credit risk management for customers.