Preventive replacement schedule: a case study at a processing industry

Ahmad, Rosmaini; Kamaruddin, Shahrul; Azid, Ishak Abdul; Almanar, Indra Putra

doi:10.1504/ijise.2011.041544

Cited by 6 publications

(5 citation statements)

References 36 publications

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“…(2011) introduces the concept of multi-objective function as optimization model to generate PM and replacement schedule with the objective of determining a set of actions for each component in the system while simultaneously minimizing the total cost and maximizing reliability. Wu and Clements-Croome (2005), Nakagawa and Mizutani (2009), Ahmad et al. (2011), Castro et al.…”

Section: Introductionmentioning

confidence: 99%

“…Kamran et al (2011) introduces the concept of multiobjective function as optimization model to generate PM and replacement schedule with the objective of determining a set of actions for each component in the system while simultaneously minimizing the total cost and maximizing reliability. Wu and Clements-Croome (2005), Nakagawa and Mizutani (2009), Ahmad et al (2011), Castro et al (2012 Seddiqe et al (2014), Lewaherilla et al (2016) and Basri et al (2017) have contributed to PM models, policies and applications. Recently, Lee et al (2019) used the conditional reliability threshold in place of the system reliability threshold for PM optimization problem.…”

Section: Introductionmentioning

confidence: 99%

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Geometric imperfect preventive maintenance and replacement (GIPMAR) model for aging repairable systems

Udoh

Effanga

2021

IJQRM

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PurposeThis work seeks to develop a geometric imperfect preventive maintenance (PM) and replacement model (GIPMAR) for aging repairable systems due to age and prolong usage that would meet users need in three phases: within average life span, beyond average life span and beyond initial replacement age of system.Design/methodology/approachThe authors utilized the geometric process (GP) as the hazard function to characterize the increasing failure rate (IFR) of the system. The GP hazard function was incorporated into the hybridized preventive and replacement model of Lin et al. (2000). The resultant expected cost rate function was optimized to obtain optimum intervals for PM/replacement and required numbers of PM per cycle. The proposed GIPMAR model was applied to repairable systems characterized by Weibull life function and the results yielded PM/replacement schedules for three different phases of system operation.FindingsThe proposed GIPMAR model is a generalization of Lin et al. (2000) PM model that were comparable with results of earlier models and is adaptive to situations in developing countries where systems are used across the three phases of operation depicted in this work. This may be due to economic hardship and operating environment.Practical implicationsThe proposed model has provided PM/Replacement schedules for different phases of operation which was never considered. This would provide a useful guide to maintenance engineers and end-users in developing countries with a view to minimizing the average cost of maintenance as well as reducing the number of down times of systems.Social implicationsA duly implemented GIPMAR model would ensure efficient operation of systems, optimum man-hour need in the organization and guarantee customer's goodwill in a competitive environment.Originality/valueIn this work, the authors have extended Lin et al. (2000) PM model to provide PM/replacement schedules for aging repairable systems which was not provided for in earlier existing models and literature.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Geometric imperfect preventive maintenance and replacement (GIPMAR) model for aging repairable systems

Udoh

Effanga

2021

IJQRM

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“…40 However, ARM has been chosen as the tool for modelling the decision criteria because BRM in most scenarios results in unnecessary replacement of equipment/components which makes the ARM technique more cost-effective. 41 Step 7. Determination of decision criteria weight: The weights of the decision criteria are evaluated using the compromise weighting technique which combines the AHP method with the statistical variance method.…”

Section: Procedures For Applying the Proposed Methodologymentioning

confidence: 99%

Section: Proposed Scheduled Replacement Interval Determination Methodmentioning

confidence: 99%

The development of a model for determining scheduled replacement intervals for marine machinery systems

Emovon

Norman

Murphy

2016

Proceedings of the Institution of Mechanical Engineers, Part M:

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One of the challenges of maintenance management of a marine machinery system is the problem of selecting the optimum interval for replacement of equipment items. Most of the approaches that are given in the literature for selecting optimum replacement intervals are based on a single criterion model such as cost. This approach may be satisfactory for some industries but for the marine industry disruption in services will result in a considerable cost penalty and, as such, other factors such as system downtime and system reliability must be taken into consideration when determining the optimum replacement interval for the system. These decision criteria have been proven to be in conflict with one another. On this basis, a multi-criteria decision-making tool, Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS), is proposed in this article for aggregating multiple criteria in order for them to be used simultaneously in determining the optimum scheduled replacement interval for the equipment items of the system. The use of a multi-criteria decision-making tool allows the decision-maker to express preference for the decision criteria in terms of their levels of importance. To achieve this aim, a compromise decision weighting technique is integrated with TOPSIS. The compromise weighting technique was obtained from a combination of the variance method (an objective decision criteria weighting technique) and analytical hierarchy process (a subjective decision criteria weighting technique). In order to demonstrate the applicability of the proposed innovative methodology for determining the optimum replacement intervals for a marine machinery system and also validate the technique, a case study involving some equipment items of a marine diesel engine is presented. Although results show that it produces the same optimum solution as the methods in the literature, the proposed method is more flexible and less computationally intensive.

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“…Kegiatan proses produksi perlu melakukan penyesuaian terhadap perkembangan teknologi untuk mendukung kinerja operasional perusahaan. Hal ini diupayakan agar perusahaan tidak mengalami masalah yang diakibatkan oleh berhentinya proses produksi [1,2]. Teknologi yang digunakan pada perusahaan manufaktur yaitu peralatan mesin yang dapat mempermudah dalam proses produksi.…”

Section: Pendahuluanunclassified

Optimasi Kapasitas Lantai Produksi Melalui Peningkatan Penerapan Preventive Maintenance Kasus Produksi Line Tile Keramik

Hidayat¹,

Sudiro

2023

teknobiz

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Preventive maintenance adalah suatu kegiatan pemeliharaan terhadap mesin yang dilakukan secara berkala untuk mencegah terjadinya kerusakan yang tidak terduga pada seluruh peralatan mesin produksi. Konsep smart maintenance system yang terdiri dari equipment preventive maintenance list, preventive maintenance, gemba management, on the job trainning dan autonomous maintenance. SMS merupakan suatu ide yang dapat diimplementasikan dengan tujuan untuk mengoptimalkan kegiatan perawatan mesin dan memudahkan dalam kontrol serta monitoring pemakaian biaya maintenance dan pendukungnya. Cara pandang baru untuk mengurangi durasi downtime dan defect adalah dengan melibatkan operator produksi dalam upaya merawat kondisi mesin yang dilakukan sehari-hari dan memfungsikan tim engineering maintenance sebagai tim pendukung dalam melakukan perawatan, perbaikan dan help service secara rutin. Sehingga performance mesin selalu terjaga, sehingga quantity dan quality output hasil produksi dapat terealisasi sesuai dengan target.

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Preventive replacement schedule: a case study at a processing industry

Cited by 6 publications

References 36 publications

Geometric imperfect preventive maintenance and replacement (GIPMAR) model for aging repairable systems

Geometric imperfect preventive maintenance and replacement (GIPMAR) model for aging repairable systems

The development of a model for determining scheduled replacement intervals for marine machinery systems

Optimasi Kapasitas Lantai Produksi Melalui Peningkatan Penerapan Preventive Maintenance Kasus Produksi Line Tile Keramik

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