سال:1394 | دوره: | شماره: |تعداد مقالات:12

In this paper, we develop a new mathematical model that integrates layout configuration and production planning in the design of dynamic distributed layouts. The model incorporates a number of important manufacturing attributes such as demand fluctuation, system reconfiguration, lot splitting, work load balancing, alternative routings, machine capability and tooling requirements. In addition, the model allows several cost elements to be optimized in an integrated manner. These costs are associated with material handling, machine relocation, setup, inventory carrying, in-house production and subcontracting needs. Numerical examples of different sizes are presented to illustrate the nature of the developed model and shed light on several managerial insights.

Within the competition in today’s business environment, the design of supply chains becomes more complex than before. This paper deals with the retailer’s location problem when customers choose their vendors, and inventory costs have been considered for retailers. In a competitive location problem, price and location of facilities affect demands of customers; consequently, simultaneous optimization of the location and inventory system is needed. To prepare a realistic model, demand and lead time have been assumed as stochastic parameters, and queuing theory has been used to develop a comprehensive mathematical model. Due to complexity of the problem, a branch and bound algorithm has been developed, and its performance has been validated in several numerical examples, which indicated effectiveness of the algorithm. Also, a real case has been prepared to demonstrate performance of the model for real world.

Service quality is often conceptualized as the comparison between service expectations and the actual performance perceptions. It enhances customer satisfaction, decreases customer defection, and promotes customer loyalty. Substantial literature has examined the concept of service quality, its dimensions, and measurement methods. We introduce the perceived service quality index (PSQI) as a single measure for evaluating the multiple-item service quality construct based on the SERVQUAL model. A slack-based measure (SBM) of efficiency with constant inputs is used to calculate the PSQI. In addition, a nonlinear programming model based on the SBM is proposed to delineate an improvement guideline and improve service quality. An empirical study is conducted to assess the applicability of the method proposed in this study. A large number of studies have used DEA as a benchmarking tool to measure service quality. These models do not propose a coherent performance evaluation construct and consequently fail to deliver improvement guidelines for improving service quality. The DEA models proposed in this study are designed to evaluate and improve service quality within a comprehensive framework and without any dependency on external data.

‘Survival of the fittest’ is the reality in modern global competition. Organizations around the globe are adopting or willing to embrace just-in-time (JIT) production to reinforce the competitiveness. Even though JIT is the most powerful inventory management methodologies it is not free from barriers. Barriers derail the implementation of JIT production system. One of the most significant tasks of top management is to identify and understand the relationship between the barriers to JIT production for alleviating its bad effects. The aims of this paper are to study the barriers hampering the implementation of successful JIT production and analysing the interactions among the barriers using interpretive structural modelling technique. Twelve barriers have been identified after reviewing literature. This paper offers a roadmap for preparing an action plan to tackle the barriers in successful implementation of JIT production.

In practice, the supplier often offers the retailers a trade credit period M and the retailer in turn provides a trade credit period N to her/his customer to stimulate sales and reduce inventory. From the retailer’s perspective, granting trade credit not only increases sales and revenue but also increases opportunity cost (i.e., the capital opportunity loss during credit period) and default risk (i.e., the percentage that the customer will not be able to pay off his/her debt obligations). Hence, how to determine credit period is increasingly recognized as an important strategy to increase retailer’s profitability. Also, the selling items such as fruits, fresh fishes, gasoline, photographic films, pharmaceuticals and volatile liquids deteriorate continuously due to evaporation, obsolescence and spoilage. In this paper, we propose an economic order quantity model for the retailer where (1) the supplier provides an up-stream trade credit and the retailer also offers a down-stream trade credit, (2) the retailer’s down-stream trade credit to the buyer not only increases sales and revenue but also opportunity cost and default risk, and (3) the selling items are perishable. Under these conditions, we model the retailer’s inventory system as a profit maximization problem to determine the retailer’s optimal replenishment decisions under the supply chain management. We then show that the retailer’s optimal credit period and cycle time not only exist but also are unique. We deduce some previously published results of other researchers as special cases. Finally, we use some numerical examples to illustrate the theoretical results.

Hospital meal carts are used to deliver meals, drugs and some other materials to patients in the hospital environment. These carts which are moved manually by operators, the health workers, mostly do not comply with ergonomics guidelines and physical requirements of the equipment users in terms of anthropometry data of the region thus increasing the risk of musculoskeletal disorder among the meal cart users. This study carried out ergonomic evaluation of the available meal carts in some western Nigeria hospitals. A well-structured questionnaire has two major segments: Operational survey and biomechanical survey, which were administered to the health workers using hospital meal carts in some hospitals in southwestern Nigeria, and physical assessment, which was undertaken to collect data for the ergonomic evaluation. The responses from the questionnaires show that some areas on the existing hospital meal carts are of concern to the users which need to be improved upon.

This paper presents a new mathematical model to solve cell formation problem in cellular manufacturing systems, where inter-arrival time, processing time, and machine breakdown time are probabilistic. The objective function maximizes the number of operations of each part with more arrival rate within one cell. Because a queue behind each machine; queuing theory is used to formulate the model. To solve the model, two metaheurstic algorithms such as modified particle swarm optimization and genetic algorithm are proposed. For the generation of initial solutions in these algorithms, a new heuristic method is developed, which always creates feasible solutions. Both metaheurstic algorithms are compared against global solutions obtained from Lingo software’s branch and bound (B&B). Also, a statistical method will be used for comparison of solutions of two metaheurstic algorithms. The results of numerical examples indicate that considering the machine breakdown has significant effect on block structures of machine-part matrixes.

In the context of industrial engineering, the predetermined time systems (PTS) play an important role in workplaces because inefficiencies are found in assembly processes that require manual manipulations. In this study, an approach is proposed with the aim to analyze time and motions in a manual process using a capture motion system embedded to a virtual environment. Capture motion system tracks IR passive markers located on the hands to take the positions of each one. For our purpose, a real workplace is virtually represented by domains to create a virtual workplace based on basic geometries. Motion captured data are combined with the virtual workplace to simulate operations carried out on it, and a time and motion analysis is completed by means of an algorithm. To test the methodology of analysis, a case study was intentionally designed using and violating the principles of motion economy. In the results, it was possible to observe where the hands never crossed as well as where the hands passed by the same place. In addition, the activities done in each zone were observed and some known deficiencies were identified in the distribution of the workplace by computational analysis. Using a frequency analysis of hand velocities, errors in the chosen assembly method were revealed showing differences in the hand velocities. An opportunity is seen to classify some quantifiable aspects that are not identified easily in a traditional time and motion analysis. The automated analysis is considered as the main contribution in this study. In the industrial context, a great application is perceived in terms of monitoring the workplace to analyze repeatability, PTS, workplace and labor activities redistribution using the proposed methodology.

Statistical process control (SPC) theory takes a negative view of adjustment of process settings, which is termed tampering. In contrast, quality and lean programmes actively encourage operators to acts of intervention and personal agency in the improvement of production outcomes. This creates a conflict that requires operator judgement: How does one differentiate between unnecessary tampering and needful intervention? Also, difficult is that operators apply tacit knowledge to such judgements. There is a need to determine where in a given production process the operators are applying tacit knowledge, and whether this is hindering or aiding quality outcomes. The work involved the conjoint application of systems engineering, statistics, and knowledge management principles, in the context of a case study. Systems engineering was used to create a functional model of a real plant. Actual plant data were analysed with the statistical methods of ANOVA, feature selection, and link analysis. This identified the variables to which the output quality was most sensitive. These key variables were mapped back to the functional model. Fieldwork was then directed to those areas to prospect for operator judgement activities. A natural conversational approach was used to determine where and how operators were applying judgement. This contrasts to the interrogative approach of conventional knowledge management. Data are presented for a case study of a meat rendering plant. The results identify specific areas where operators’ tacit knowledge and mental model contribute to quality outcomes and untangles the motivations behind their agency. Also evident is how novice and expert operators apply their knowledge differently. Novices were focussed on meeting throughput objectives, and their incomplete understanding of the plant characteristics led them to inadvertently sacrifice quality in the pursuit of productivity in certain situations. Operators’ responses to the plant are affected by their individual mental models of the plant, which differ between operators and have variable validity. Their behaviour is also affected by differing interpretations of how their personal agency should be applied to the achievement of production objectives. The methodology developed here is an integration of systems engineering, statistical analysis, and knowledge management. It shows how to determine where in a given production process the operator intervention is occurring, how it affects quality outcomes, and what tacit knowledge operators are using. It thereby assists the continuous quality improvement processes in a different way to SPC. A second contribution is the provision of a novel methodology for knowledge management, one that circumvents the usual codification barriers to knowledge management.

In this paper, the classical economic production quantity (EPQ) model is developed for non-instantaneous deteriorating items by considering a relationship between the holding cost and the ordering cycle length. Two models are developed. First, the proposed model is considered when backorders are not permitted and this condition is waived for the second case. The cost functions associated with these models are proved to be convex and an algorithm is designed to find the optimum solutions of the proposed model. Results show that the relationship between holding cost and ordering cycle length has a significant impact on the optimal lot size and total cost in the EPQ model. Numerical examples are presented to demonstrate the utility of the models.

The nurse scheduling problem (NSP) has received a great amount of attention in recent years. In the NSP, the goal is to assign shifts to the nurses in order to satisfy the hospital’s demand during the planning horizon by considering different objective functions. In this research, we focus on maximizing the nurses’ preferences for working shifts and weekends off by considering several important factors such as hospital’s policies, labor laws, governmental regulations, and the status of nurses at the end of the previous planning horizon in one of the largest hospitals in Iran i.e., Milad Hospital. Due to the shortage of available nurses, at first, the minimum total number of required nurses is determined. Then, a mathematical programming model is proposed to solve the problem optimally. Since the proposed research problem is NP-hard, a meta-heuristic algorithm based on simulated annealing (SA) is applied to heuristically solve the problem in a reasonable time. An initial feasible solution generator and several novel neighborhood structures are applied to enhance performance of the SA algorithm. Inspired from our observations in Milad hospital, random test problems are generated to evaluate the performance of the SA algorithm. The results of computational experiments indicate that the applied SA algorithm provides solutions with average percentage gap of 5.49% compared to the upper bounds obtained from the mathematical model. Moreover, the applied SA algorithm provides significantly better solutions in a reasonable time than the schedules provided by the head nurses.

In the present work, an experimental investigation on wire electrical discharge machining (WEDM) of Monel-400 has been presented. Monel-400 is a nickel– copper-based alloy, mostly employed in ships and corrosion-resisting applications. Four input WEDM parameters namely discharge current (Ip), pulse-on time (Ton), pulseoff time (Toff) and servo voltage (SV) have been investigated and modeled for two performance characteristics namely machining rate (MR) and surface roughness (SR). Effect of WEDM parameters has been discussed using response surface graphs. Using analysis of variance, quadratic model is found significant for MR while two factors interaction (2FI) model has been suggested for SR. To optimize multi-performance characteristics, desirability function has been employed. Corresponding to highest desirability, the optimal combination of discharge parameters is Ip: 103 A; Ton: 113 ms; Toff: 37 ms and SV: 50 V. The effect of discharge energy on surface morphology has also been examined. High discharge energy increases the extent of surface damage and results in large size and overlapped craters on machined surface. Low discharge energy and high value of Toff result in minimum defects on machined surface. Trim cutting operations were performed at low discharge energy using different wire offset values. Result shows that surface finish can be improved significantly after a single trim cut irrespective of high discharge energy in rough cut.