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Article
Publication date: 7 May 2019

Shao Xiao, Zhixiang Chen and Bhaba R. Sarker

Equipment reliability significantly impacts productivity, and in order to obtain high equipment reliability and productivity, maintenance and production decision should be…

Abstract

Purpose

Equipment reliability significantly impacts productivity, and in order to obtain high equipment reliability and productivity, maintenance and production decision should be made simultaneously to keep manufacturing system healthy. The purpose of this paper is to investigate the joint optimization of equipment maintenance and production decision for k-out-of-n system equipment with attenuation of product quality and to explore the impact of maintenance on the production and cost control for manufacturers.

Design/methodology/approach

A multi-period Markov chain model for k-out-of-n system equipment is set up based on the assumption that the deterioration of equipment is a pure birth process. Then, the maintenance cost, setup cost, inventory holding cost, shortage cost, production cost and the quality cost are analyzed with the uncertain demand and the attenuation of product quality stemmed from equipment deterioration. The total lowest cost per unit time and its specific calculation method are presented. Finally, the robustness and flexibility of the method are verified by a numerical example and the effects of equipment deterioration intensity and attenuation of product quality are analyzed.

Findings

The result shows that the joint decision model could not only satisfy the uncertain demand with low cost and strong robustness but also make the output products high quality level. In addition, the attenuation of product quality would influence the equipment maintenance and production decision and leads to the production waste and increases the operation cost greatly.

Originality/value

Implications derived from this study can help production maintenance managers and reliability engineers adequately select maintenance policy to improve the equipment efficiency and productivity with high quality level at a relatively low cost.

Details

International Journal of Quality & Reliability Management, vol. 36 no. 5
Type: Research Article
ISSN: 0265-671X

Keywords

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Article
Publication date: 22 July 2019

Xinfeng Lai, Zhixiang Chen and Bhaba R. Sarker

The purpose of this paper is to study a production lot sizing problem with consideration of imperfect manufacturing and emergency maintenance policy, providing managerial…

Abstract

Purpose

The purpose of this paper is to study a production lot sizing problem with consideration of imperfect manufacturing and emergency maintenance policy, providing managerial implication for practitioners.

Design/methodology/approach

In this study, the authors introduce two models, where in Model I, shortages are not allowed and repair times are negligible. In Model II, shortages are allowed and are partially backlogged, and repair times are assumed to be exponentially distributed, algorithm is developed to solve the models, numerical examples were demonstrated the applications.

Findings

Results show that in the Model I, demand rate is the most significant parameter affecting the average expected cost, whereas the time needed to breakdown after machine shift is the most significant factor affecting the production lot size. Therefore, reduction in the time needed to breakdown after machine shift would be helpful for determining an appropriate production lot size in Model I. In Model II, repair time parameter is the most significant factor affecting the average expected cost. Reducing the value of machine shift parameter would be helpful for determining an adequate production lot size and reducing decision risk.

Practical implications

This paper can provide important reference value for practitioners with managerial implication of how to effectively maintain equipment, i.e. how to make product lot size considering the influence of the maintenance policy.

Originality/value

From the aspect of academia, this paper provides a solution to the optimal production lot sizing decision for an imperfect manufacturing system with consideration of machine breakdown and emergency maintenance, which is a supplement to imperfect EMQ model.

Details

Kybernetes, vol. 49 no. 5
Type: Research Article
ISSN: 0368-492X

Keywords

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Article
Publication date: 1 December 1997

Bhaba R. Sarker and Kun Li

Presents a mixed‐integer programme to simultaneously select part routeings and form machine cells in the presence of alternate process plans so that the total cost of…

Abstract

Presents a mixed‐integer programme to simultaneously select part routeings and form machine cells in the presence of alternate process plans so that the total cost of operating and intercell material handling is minimized. Demand for parts, machine capacities, number of cells to be formed, and number of machines in a cell are included in the model. Includes an example to illustrate the solution technique of the problem of practical instance.

Details

Integrated Manufacturing Systems, vol. 8 no. 6
Type: Research Article
ISSN: 0957-6061

Keywords

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Article
Publication date: 1 October 1998

Eileen Bordelon Hoff and Bhaba R. Sarker

Automated guide vehicles (AGVs) are driverless vehicles that perform material handling operations in both flexible and conventional facilities. We provide here a review of…

Abstract

Automated guide vehicles (AGVs) are driverless vehicles that perform material handling operations in both flexible and conventional facilities. We provide here a review of recent work on the design of AGV guide paths and dispatching rules, including related issues such as idle vehicle location, and location of pickup and delivery stations. Different types of guide paths and related layouts, including optimal and heuristic approaches to the path design, are reviewed here. Dispatching rules and algorithms, including zone control, are also proposed and compared with commonly‐used rules.

Details

Integrated Manufacturing Systems, vol. 9 no. 5
Type: Research Article
ISSN: 0957-6061

Keywords

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Article
Publication date: 1 December 1995

Bhaba R. Sarker and Junfang Yu

Service systems that require failure rate below a predeterminedvalue usually need maintenance in order to operate at that level ofreliability. One major issue in…

Abstract

Service systems that require failure rate below a predetermined value usually need maintenance in order to operate at that level of reliability. One major issue in maintenance systems is the optimal maintenance schedule that incurs minimum total cost. Considering fixed inflation rate and failure rate variation after maintenance, an algorithm of balanced maintenance scheduling is developed. The algorithm provides an optimal number of replacement and preventive maintenance to minimize the total maintenance cost over a certain planning period. A numerical example is demonstrated and compared with the results reported by other researchers.

Details

International Journal of Quality & Reliability Management, vol. 12 no. 9
Type: Research Article
ISSN: 0265-671X

Keywords

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Article
Publication date: 16 November 2015

Zhixiang Chen and Bhaba R. Sarker

The purpose of this paper is to study the impact of learning effect and demand uncertainty on aggregate production planning (APP), provide practitioners with some…

Abstract

Purpose

The purpose of this paper is to study the impact of learning effect and demand uncertainty on aggregate production planning (APP), provide practitioners with some important managerial implications for improving production planning and productivity.

Design/methodology/approach

Motivated by the background of one labour-intensive manufacturing firm – a mosquito expellant factory – an APP model considering workforce learning effect and demand uncertainty is established. Numerical example and comparison with other two models without considering learning and uncertainty of demand are conducted.

Findings

The result shows that taking into account the uncertain demand and learning effect can reduce total production cost and increase flexibility of APP.

Practical implications

Managerial implications are provided for practitioners with four propositions on improving workforce learning effect, i.e. emphasizing employee training, combing individual and organizational learning and reduction of forgetting effect.

Originality/value

This paper has practice value in improving APP in labor-intensive manufacturing.

Details

Journal of Modelling in Management, vol. 10 no. 3
Type: Research Article
ISSN: 1746-5664

Keywords

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