International Journal of Collaborative Enterprise http://www.inderscience.com/browse/index.php?journalID=82&year=2011&vol=2&issue=4 Inderscience Publishers Ltd en-uk International Journal of Collaborative Enterprise 1740-2085 1740-2093 © 2011 Inderscience Publishers Ltd editor@inderscience.com https://www.inderscience.com/images/files/coverImgs/ijcent_scoverijcent.jpg http://www.inderscience.com/browse/index.php?journalID=82&year=2011&vol=2&issue=4 http://www.inderscience.com/link.php?id=43823 Maintenance management has become one of the most important functions in an organisation. The main objective of maintenance is to keep machine resources running by increasing the availability through repair activities as in corrective maintenance or some proactive activities as in preventive maintenance. According to the literature, maintenance management is explored in several areas. A comprehensive review of some researches in the area of maintenance and quality is presented in this article. Maintenance planning and management: a state of the art survey
Hazem Smadi; Ali K. Kamrani
International Journal of Collaborative Enterprise, Vol. 2, No. 4 (2011) pp. 227 - 250
Maintenance management has become one of the most important functions in an organisation. The main objective of maintenance is to keep machine resources running by increasing the availability through repair activities as in corrective maintenance or some proactive activities as in preventive maintenance. According to the literature, maintenance management is explored in several areas. A comprehensive review of some researches in the area of maintenance and quality is presented in this article.

]]> 10.1504/IJCENT.2011.043823 International Journal of Collaborative Enterprise, Vol. 2, No. 4 (2011) pp. 227 - 250 Hazem Smadi; Ali K. Kamrani Design and Free Form Fabrication Laboratory, University of Houston, Houston, TX 77204, USA. ' Design and Free Form Fabrication Laboratory, University of Houston, Houston, TX 77204, USA; FARCAMT, Industrial Engineering Department, King Saud University, 11421 P.O. Box 800, Riyadh, Saudi Arabia maintenance planning reliability centred maintenance preventive maintenance fault propagation trees strategic planning machine resources machine availability repair activities corrective maintenance proactive activities maintenance modelling maintenance management collaborative enterprises collaboration. 2011-11-23T23:20:50-05:00 2 4 227 250 2011-11-23T23:20:50-05:00 http://www.inderscience.com/link.php?id=43824 Maintenance actions are very important for all industries and manufacturers. The minimum maintenance cost with good maintenance actions is a target goal of all manufacturers on the basis that we cannot entirely avoid machine failures. Nevertheless, do more maintenance, will reduce chances of machine breakdowns but will produce more maintenance cost. Contrary, do less maintenance, will produce less maintenance cost but has more changes to face with machine breakdowns. Then, the optimal maintenance policy will be helpful for solving this problem. Thus, this study and its model formulations are mainly interested on the methodology of sharing maintenance downtime between preventive and corrective maintenance under the given availability. This will be helpful for reducing the maintenance cost under the given certain availability. Therefore, the approach has emphasised with repair rate, maintenance downtime and to be concerned with the maintenance actions under the given availability. Furthermore, the heuristics are solved by the Lagrange multiplier approach, and based on the arrangement of maintainability between preventive and corrective maintenances. Additionally, the complex realistic scenarios of the maintenance optimisation will be the solution which will be useful and to be the benefit for reducing the total maintenance cost, unplanned stoppage, and reduce the contingencies from machine failure. The heuristics of effective maintenance policy under the given availability
Sakon Wongmongkolrit; Bordin Rassameethes
International Journal of Collaborative Enterprise, Vol. 2, No. 4 (2011) pp. 251 - 262
Maintenance actions are very important for all industries and manufacturers. The minimum maintenance cost with good maintenance actions is a target goal of all manufacturers on the basis that we cannot entirely avoid machine failures. Nevertheless, do more maintenance, will reduce chances of machine breakdowns but will produce more maintenance cost. Contrary, do less maintenance, will produce less maintenance cost but has more changes to face with machine breakdowns. Then, the optimal maintenance policy will be helpful for solving this problem. Thus, this study and its model formulations are mainly interested on the methodology of sharing maintenance downtime between preventive and corrective maintenance under the given availability. This will be helpful for reducing the maintenance cost under the given certain availability. Therefore, the approach has emphasised with repair rate, maintenance downtime and to be concerned with the maintenance actions under the given availability. Furthermore, the heuristics are solved by the Lagrange multiplier approach, and based on the arrangement of maintainability between preventive and corrective maintenances. Additionally, the complex realistic scenarios of the maintenance optimisation will be the solution which will be useful and to be the benefit for reducing the total maintenance cost, unplanned stoppage, and reduce the contingencies from machine failure.

]]> 10.1504/IJCENT.2011.043824 International Journal of Collaborative Enterprise, Vol. 2, No. 4 (2011) pp. 251 - 262 Sakon Wongmongkolrit; Bordin Rassameethes International Graduate Program of Industrial Engineering (IGPIE), Faculty of Engineering, Kasetsart University, Bangkhen Campus, Bangkok 10900, Thailand. ' Operations Management Department, Faculty of Business Administration, Kasetsart University, Bangkhen, Bangkok, 10900, Thailand maintenance policies heuristics given availability maintenance actions maintenance costs machine failures machine breakdowns optimal maintenance downtime sharing maintenance downtime preventive maintenance corrective maintenance cost reduction repair rates Lagrange multipliers mathematical optimisation Joseph Lagrange maintainability unplanned stoppages contingency reduction collaborative enterprises collaboration maintenance modelling maintenance management. 2011-11-23T23:20:50-05:00 2 4 251 262 2011-11-23T23:20:50-05:00 http://www.inderscience.com/link.php?id=43825 'Burn-in/preventive maintenance' programme is an efficient approach used to minimise the warranty servicing cost of a product with bathtub shaped failure rate. Burn-in is a widely used method to improve the quality of product during its 'infant mortality' period and preventive maintenance is a scheduled necessary activity carried out during its 'wear-out' period. In this paper, an optimisation model is developed to determine the optimal burn-in time and optimal imperfect preventive maintenance strategy that minimises the total mean servicing cost of a warranted product with an age-dependent repair cost. We provide a numerical study to illustrate our results. Optimal burn-in time and imperfect maintenance strategy for a warranted product with bathtub shaped failure rate
Mahmood Shafiee; Ezzatollah Asgharizadeh
International Journal of Collaborative Enterprise, Vol. 2, No. 4 (2011) pp. 263 - 274
'Burn-in/preventive maintenance' programme is an efficient approach used to minimise the warranty servicing cost of a product with bathtub shaped failure rate. Burn-in is a widely used method to improve the quality of product during its 'infant mortality' period and preventive maintenance is a scheduled necessary activity carried out during its 'wear-out' period. In this paper, an optimisation model is developed to determine the optimal burn-in time and optimal imperfect preventive maintenance strategy that minimises the total mean servicing cost of a warranted product with an age-dependent repair cost. We provide a numerical study to illustrate our results.

]]> 10.1504/IJCENT.2011.043825 International Journal of Collaborative Enterprise, Vol. 2, No. 4 (2011) pp. 263 - 274 Mahmood Shafiee; Ezzatollah Asgharizadeh Department of Industrial Engineering, Faculty of Engineering, Tarbiat Modares University, P.O. Box 14115-179, Tehran, Iran. ' Department of Industrial Management, University of Tehran, P.O. Box 14155-6311, Tehran, Iran bathtub curve reliability engineering failure rates burn-in times preventive maintenance minimal repairs servicing costs imperfect strategies warranted products warranty servicing warranties maintenance strategies product quality infant mortality failures scheduled activities necessary activities wear-out periods optimisation models cost minimisation age-dependent repairs repair costs collaborative enterprises collaboration maintenance modelling maintenance management. 2011-11-23T23:20:50-05:00 2 4 263 274 2011-11-23T23:20:50-05:00 http://www.inderscience.com/link.php?id=43826 Most of continuous process industries tend to arbitrary shorting the duration of shutdown maintenance and return back to production state in order to reduce the maintenance cost or to increase the profit by taking advantage of high market demand and prices of their products. By arbitrary shorting the duration of shutdown maintenance, the plants in these industries expose themselves to unplanned stoppages of their production system. These unplanned stoppages will cause harm to the inside and outside environments and it will sharply affect the company profit. The proposed mathematical model developed in this paper aims at finding out the best period for performing shutdown maintenance. It is based on determining the period of time during the predetermined time horizon for performing shutdown maintenance activities in which the maintenance cost and the loss of production that is caused by shutdown maintenance are in their lowest levels. Best period of time for performing shutdown maintenance
Adel M. Al-Shayea
International Journal of Collaborative Enterprise, Vol. 2, No. 4 (2011) pp. 275 - 283
Most of continuous process industries tend to arbitrary shorting the duration of shutdown maintenance and return back to production state in order to reduce the maintenance cost or to increase the profit by taking advantage of high market demand and prices of their products. By arbitrary shorting the duration of shutdown maintenance, the plants in these industries expose themselves to unplanned stoppages of their production system. These unplanned stoppages will cause harm to the inside and outside environments and it will sharply affect the company profit. The proposed mathematical model developed in this paper aims at finding out the best period for performing shutdown maintenance. It is based on determining the period of time during the predetermined time horizon for performing shutdown maintenance activities in which the maintenance cost and the loss of production that is caused by shutdown maintenance are in their lowest levels.

]]> 10.1504/IJCENT.2011.043826 International Journal of Collaborative Enterprise, Vol. 2, No. 4 (2011) pp. 275 - 283 Adel M. Al-Shayea Industrial Engineering Department, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Kingdom of Saudi Arabia maintenance costs production loss predetermined time horizons maintenance timing shutdown maintenance continuous process industries arbitrary shorting production state cost reduction profits high demand market demand product prices industrial plants unplanned stoppages production systems mathematical models collaborative enterprises collaboration maintenance modelling maintenance management. 2011-11-23T23:20:50-05:00 2 4 275 283 2011-11-23T23:20:50-05:00 http://www.inderscience.com/link.php?id=43827 In this paper, we investigate a hybrid minimal repair and age replacement policy for a repairable product sold with a two-dimensional non-renewing failure replacement warranty. We first model product failures using the one-dimensional approach and then use a more appropriate formulation to model the effect of age and usage to the product degradation. Under this policy, for a given usage rate y, the product is directly repaired minimally when it fails in (0, S<SUB align=“right”>y] and replaced with the new one on the first failure in (S<SUB align=“right”>y, ?<SUB align=“right”>y] or when its age reaches ?<SUB align=“right”>y, whichever occurs first. We obtain the global optimal solution of S<SUB align=“right”>y, for a given ?<SUB align=“right”>y which minimises the expected cost per unit time to the buyer. We present numerical examples to illustrate the properties of the optimal solution. Hybrid minimal repair and age replacement policy for two-dimensional warranted products
H. Husniah; U.S. Pasaribu; A.H. Halim; B.P. Iskandar
International Journal of Collaborative Enterprise, Vol. 2, No. 4 (2011) pp. 284 - 301
In this paper, we investigate a hybrid minimal repair and age replacement policy for a repairable product sold with a two-dimensional non-renewing failure replacement warranty. We first model product failures using the one-dimensional approach and then use a more appropriate formulation to model the effect of age and usage to the product degradation. Under this policy, for a given usage rate y, the product is directly repaired minimally when it fails in (0, S<SUB align=“right”>y] and replaced with the new one on the first failure in (S<SUB align=“right”>y, ?<SUB align=“right”>y] or when its age reaches ?<SUB align=“right”>y, whichever occurs first. We obtain the global optimal solution of S<SUB align=“right”>y, for a given ?<SUB align=“right”>y which minimises the expected cost per unit time to the buyer. We present numerical examples to illustrate the properties of the optimal solution.

]]> 10.1504/IJCENT.2011.043827 International Journal of Collaborative Enterprise, Vol. 2, No. 4 (2011) pp. 284 - 301 H. Husniah; U.S. Pasaribu; A.H. Halim; B.P. Iskandar Department of Industrial Engineering, Bandung Institute of Technology, Bandung 40132, Indonesia; Department of Industrial Engineering, Langlangbuana University, Bandung 40132, Indonesia. ' Department of Mathematics and Natural Sciences, Bandung Institute of Technology, Bandung 40132, Indonesia. ' Department of Industrial Engineering, Bandung Institute of Technology, Bandung 40132, Indonesia. ' Department of Industrial Engineering, Bandung Institute of Technology, Bandung 40132, Indonesia hybrid repairs minimal repairs age replacement usage rates warranted products two-dimensional warranties repairable products non-renewing warranties failure replacement warranties product failures one-dimensional approaches product degradation optimal solutions expected costs unit time renewal reward theorems optimisation collaborative enterprises collaboration maintenance modelling maintenance management. 2011-11-23T23:20:50-05:00 2 4 284 301 2011-11-23T23:20:50-05:00 http://www.inderscience.com/link.php?id=43828 There has been a considerable progress in condition-based maintenance (CBM) in which maintenance actions are carried out as warranted by the condition of machines to reduce the associated maintenance costs and increase the availability of machines. If the maintenance activities are carried out individually, setup costs would be higher and the system downtime would be longer than if the maintenance activities are carried out together on a group of machines. So, finding an optimal grouping policy is an important problem in itself. This paper investigates a Q-learning algorithm to come up with a grouping policy that would reduce set up costs and increase the uptime efficiency of a flow line manufacturing system. The breakdown of even a single machine in a flow line system could affect the availability of the entire system, particularly when there are no storage buffers in between successive machines. The results reported here show that proposed Q-learning-based grouping policy is capable of reducing the number of repair or maintenance interruptions considerably. A Q-learning-based adaptive grouping policy for condition-based maintenance of a flow line manufacturing system
Yusuf Ozbek; Abe Zeid; Sagar Kamarthi
International Journal of Collaborative Enterprise, Vol. 2, No. 4 (2011) pp. 302 - 321
There has been a considerable progress in condition-based maintenance (CBM) in which maintenance actions are carried out as warranted by the condition of machines to reduce the associated maintenance costs and increase the availability of machines. If the maintenance activities are carried out individually, setup costs would be higher and the system downtime would be longer than if the maintenance activities are carried out together on a group of machines. So, finding an optimal grouping policy is an important problem in itself. This paper investigates a Q-learning algorithm to come up with a grouping policy that would reduce set up costs and increase the uptime efficiency of a flow line manufacturing system. The breakdown of even a single machine in a flow line system could affect the availability of the entire system, particularly when there are no storage buffers in between successive machines. The results reported here show that proposed Q-learning-based grouping policy is capable of reducing the number of repair or maintenance interruptions considerably.

]]> 10.1504/IJCENT.2011.043828 International Journal of Collaborative Enterprise, Vol. 2, No. 4 (2011) pp. 302 - 321 Yusuf Ozbek; Abe Zeid; Sagar Kamarthi Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA 02115, USA. ' Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA 02115, USA. ' Department of Mechanical and Industrial Engineering, Northeastern University, Boston, MA 02115, USA Q-learning reinforcement learning condition-based maintenance grouping policies group maintenance adaptive groupings flow line manufacturing maintenance actions machine conditions maintenance costs machine availability maintenance activities setup costs system downtimes algorithms uptime efficiency machine breakdowns system availability storage buffers successive machines repair interruptions maintenance interruptions collaborative enterprises collaboration maintenance modelling maintenance management. 2011-11-23T23:20:50-05:00 2 4 302 321 2011-11-23T23:20:50-05:00