TY - JOUR
T1 - A hybrid of industrial maintenance decision making grids
AU - Yunusa-Kaltungo, Akilu
AU - Labib, Ashraf
N1 - EMBARGO 12 MTHS - 27 Mar 2021
This is an Accepted Manuscript of an article published in Production Planning and Control, (2020), available online: http://www.tandfonline.com/10.1080/09537287.2020.1741046
DOI not yet working - 10.1080/09537287.2020.1741046
PY - 2020/3/26
Y1 - 2020/3/26
N2 - It is fair to assume that the main challenge in maintenance decision making is the existence of a gap between theory and sustainable practice which is attributable to complexity, too much emphasis on development of new models that only serve to criticise earlier ones, underrepresentation of case study-based researches and lack of adequate incorporation of industry-based knowledge into most theoretical studies. In this paper, we revisited the application of the decision making grid (DMG) for maintenance optimisation but the main novelty here is to harmonise the strengths of the two most popular DMG approaches as opposed to the previous trends of advocating one over the other. Additionally, the current initiative limits assumptions associated with the process, since both DMG approaches depend on the main objective and nature of data involved. The data required for implementation are frequency of breakdown events and downtime for each event, which is readily available in all computerized maintenance management systems. This implies that we rely on just having access to some sort of a counter of faults and a timer for each event.
AB - It is fair to assume that the main challenge in maintenance decision making is the existence of a gap between theory and sustainable practice which is attributable to complexity, too much emphasis on development of new models that only serve to criticise earlier ones, underrepresentation of case study-based researches and lack of adequate incorporation of industry-based knowledge into most theoretical studies. In this paper, we revisited the application of the decision making grid (DMG) for maintenance optimisation but the main novelty here is to harmonise the strengths of the two most popular DMG approaches as opposed to the previous trends of advocating one over the other. Additionally, the current initiative limits assumptions associated with the process, since both DMG approaches depend on the main objective and nature of data involved. The data required for implementation are frequency of breakdown events and downtime for each event, which is readily available in all computerized maintenance management systems. This implies that we rely on just having access to some sort of a counter of faults and a timer for each event.
KW - Manufacturing systems
KW - industrial maintenance
KW - decision analysis
KW - decision making grid
KW - maintenance strategies
KW - case study
U2 - 10.1080/09537287.2020.1741046
DO - 10.1080/09537287.2020.1741046
M3 - Article
SN - 0953-7287
VL - 32
SP - 397
EP - 414
JO - Production Planning and Control
JF - Production Planning and Control
IS - 5
ER -