Adaptive and noncyclic preventive maintenance to augment production activities

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Sunil Dutta ◽  
Narala Suresh Kumar Reddy

PurposeProduction schedules, if not met as per timelines may result in heavy losses to a company in terms of its standing and the overall profit. Production scheduling is generally planned by not taking preventive maintenance schedules into consideration. Most of the plants allocate discrete hours/time for preventive maintenance activities. These hours allocated for preventive maintenance will be in addition to the hours which would be lost during breakdown maintenance. These lost hours may be reduced if production scheduling and preventive maintenance activities are integrated. This advocates that we need to devise a methodology which can take care of lost hours.Design/methodology/approachAdaptive and noncyclic maintenance strategy describes the modification of existing maintenance practices, policies and procedures to meet new dynamic tasks/opportunities. It demands a high degree of flexibility and mental agility from maintenance staff members. The maintenance team has to be on a lookout for an opportunity message received from the central server and has to act promptly. The moment an opportunity arises, a message is forwarded to a central maintenance server (opportunity is captured). The central server then assigns individuals/team, based on their expertise and the maintenance task due on that machine/equipment. This action is completely automated and implemented without delay.FindingsThe total man-hours saved by executing adaptive and noncyclic preventive maintenance methodology comes to 705 h during 15 days on 30 machines installed in three different sections. There was a contribution of 71 innovative ideas from the repair teams. Out of these 71 innovative ideas, 16 were found suitable for execution. A quantum jump in the morale and motivation of the maintenance team was noticed from the feedback forms. Mutual understanding and respect for each other among employees has been enhanced. The optimization of resources and infrastructure including tools, gauges, testing equipment, etc. could truly be attained.Practical implicationsThe developed adaptive and noncyclic preventive maintenance model assists in capturing lost hours and make the system proactive and lean. The suggested model optimizes the preventive and predictive maintenance activities and results in substantial saving of efforts, manpower, resources and allocated budget.Originality/valueThe adaptive and noncyclic preventive maintenance model discussed in the article is a novel approach for the optimization of resources. The technique assists in capturing lost hours and utilization of these hours for preventive maintenance tasks. The model will also encourage creative and innovative ideas from employees and take the organization toward Continual Maintenance Optimization.

2018 ◽  
Vol 35 (9) ◽  
pp. 2052-2079 ◽  
Author(s):  
Umamaheswari E. ◽  
Ganesan S. ◽  
Abirami M. ◽  
Subramanian S.

Purpose Finding the optimal maintenance schedules is the primitive aim of preventive maintenance scheduling (PMS) problem dealing with the objectives of reliability, risk and cost. Most of the earlier works in the literature have focused on PMS with the objectives of leveling reserves/risk/cost independently. Nevertheless, very few publications in the current literature tackle the multi-objective PMS model with simultaneous optimization of reliability, and economic perspectives. Since, the PMS problem is highly nonlinear and complex in nature, an appropriate optimization technique is necessary to solve the problem in hand. The paper aims to discuss these issues. Design/methodology/approach The complexity of the PMS problem in power systems necessitates a simple and robust optimization tool. This paper employs the modern meta-heuristic algorithm, namely, Ant Lion Optimizer (ALO) to obtain the optimal maintenance schedules for the PMS problem. In order to extract best compromise solution in the multi-objective solution space (reliability, risk and cost), a fuzzy decision-making mechanism is incorporated with ALO (FDMALO) for solving PMS. Findings As a first attempt, the best feasible maintenance schedules are obtained for PMS problem using FDMALO in the multi-objective solution space. The statistical measures are computed for the test systems which are compared with various meta-heuristic algorithms. The applicability of the algorithm for PMS problem is validated through statistical t-test. The statistical comparison and the t-test results reveal the superiority of ALO in achieving improved solution quality. The numerical and statistical results are encouraging and indicate the viability of the proposed ALO technique. Originality/value As a maiden attempt, FDMALO is used to solve the multi-objective PMS problem. This paper fills the gap in the literature by solving the PMS problem in the multi-objective framework, with the improved quality of the statistical indices.


2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Kaustav Kundu ◽  
Fabiana Cifone ◽  
Federica Costa ◽  
Alberto Portioli-Staudacher ◽  
Matteo Rossini

PurposeThe purpose of this paper is to provide the description of an original framework for maintenance management plan development. The research aims to use in an integrated way different World Class Manufacturing (WCM)-based tools, in order to obtain a model which can be used for preventive maintenance in different industrial contexts.Design/methodology/approachIn this research, a conceptual framework of preventive maintenance was described and then it was evaluated through a qualitative study in an Italian company. The company was chosen based on an initial interview with the operations team and the model area was selected. Then, the location was reorganized in order to obtain a green field which could sustain the implementation of the framework tools.FindingsThe case study was carried out in a small-medium manufacturing company which produces quick-release couplings and multiconnections, ranging from medium to ultra-high pressure. The defined framework has proved to be easy to implement in a company with a corrective maintenance plan, allowing the maintenance department to embrace the preventive maintenance culture. The maintenance model has been well received from the employees.Practical implicationsThe framework allows a standardization of maintenance plans. Firstly, the standardization design itself allows finding previous wastes and consequent improvement areas. Then, it brings the improvement of a single machine which impacts all other machines in its family.Originality/valueThe added value of this study is the ability to integrate different WCM-based tools. Since the framework depicts a step-by-step process; it is also a starting point for companies that want to approach preventive maintenance for the first time.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Pavel Jahoda ◽  
Radim Bris

PurposeThe paper aims to explore unavailability of dormant systems that are under both preventive and corrective maintenance. Preventive maintenance is considered as a failure based maintenance model, where full renew is realized at the occurrence of every nth failure. It proposes the imperfect corrective maintenance model, where each restoration process deteriorates the system lifetime, probability distribution of which is gradually changed via increasing failure rate.Design/methodology/approachBasic reliability mathematics necessary for unavailability quantification of a system which undergoes a real aging process with maintenance has been derived proceeding from renewal theory. New renewal cycle was defined to cover the real aging process and the expectation of its length was determined. All events resulting in the failure of studied system were explored to determine their probabilities. An integral equation where the unavailability function characterizing studied system is its solution was derived.FindingsPreventive maintenance is closely connected with the occurrence of the nth failure, which starts its renew. The number n can be considered as a parameter which significantly influences the unavailability course. The paper shows that the real aging process characterized by imperfect repairs can significantly increase the unavailability courses in contrast with theoretical aging. This is true for both monitored and dormant systems.Originality/valueAlthough mathematical methods used in this article were inspired and influenced by the work of reference (van der Weide and Pandey, 2015), derivation of final formulas for unavailability quantification considering the new renewal cycle is original. Idea of the real aging process is new as well. This paper fulfils an identified need to manage the maintenance of realistically aging systems.


2014 ◽  
Vol 20 (4) ◽  
pp. 453-470 ◽  
Author(s):  
Behnam Emami-Mehrgani ◽  
Sylvie Nadeau ◽  
Jean-Pierre Kenné

Purpose – The analysis of the optimal production and preventive maintenance with lockout/tagout planning problem for a manufacturing system is presented in this paper. The considered manufacturing system consists of two non-identical machines in passive redundancy producing one type of part. These machines are subject to random breakdowns and repairs. The purpose of this paper is to minimize production, inventory, backlog and maintenance costs over an infinite planning horizon; in addition, it aims to verify the influence of human reliability on the inventory levels for illustrating the importance of human error during the maintenance and lockout/tagout activities. Design/methodology/approach – This paper is different compared to other research projects on preventive maintenance and lockout/tagout. The influence of human error on lockout/tagout as well as on preventive maintenance activities are presented in this paper. The preventive maintenance policy depends on the machine age. For the considered manufacturing system the optimality conditions are provided, and numerical methods are used to obtain machine age-dependent optimal control policies (production and preventive maintenance rates with lockout/tagout). Numerical examples and sensitivity analysis are presented to illustrate the usefulness of the proposed approach. The system capacity is described by a finite-state Markov chain. Findings – The proposed model taking into account the preventive maintenance activities with lockout/tagout and human error jointly, instead of taking into account separately. It verifies the influence of human error during preventive maintenance and lockout/tagout activities on the optimal safety stock levels using an extension of the hedging point structure. Practical implications – The model proposed in this paper might be extended to manufacturing systems, but a number of conditions must be met to make effective use of it. Originality/value – The originality of this paper is to consider the preventive maintenance activities with lockout/tagout and human error simultaneously. The control policy is obtained in order to find the solution for the considered manufacturing system. This paper also brings a new vision on the importance of human reliability during preventive maintenance and lockout/tagout activities.


Author(s):  
Muhammad Arizki Zainul Ramadhan ◽  
Tedjo Sukmono

With the increasing needs of productivity and the use of high technology in the form of machines and production facilities, the need for maintenance functions is growing. At PT. Surabaya Wire that produces nails and wires of problems that arise especially related to damage to nail making machine, it causes the hours to stop (downtime) and delay in the production process so that the engine performance becomes less effective. The purpose of the research is to determine the time interval schedule of care and know the action or maintenance activities to be done. To solve the problem in this research using Reliability Centered Maintenance (RCM) II method with Failure Modes and Effect Analyze (FMEA) calculation. RCM II defined a process used to determine what should be done for machine maintenance, whereas for FMEA it is defined as a method to identify the highest failure form on any machine malfunction. From the calculation result using FMEA and RCM II, we got treatment interval result on side shaft component (metal handlebar) with maintenance interval for 63 hours, for crank shaft component (metal road) with maintenance interval for 81 hours, and for Electric motor component with maintenance interval for 374 hours.


2017 ◽  
Vol 27 (6) ◽  
pp. 1249-1265 ◽  
Author(s):  
Yijun Liu ◽  
Guiyong Zhang ◽  
Huan Lu ◽  
Zhi Zong

Purpose Due to the strong reliance on element quality, there exist some inherent shortcomings of the traditional finite element method (FEM). The model of FEM behaves overly stiff, and the solutions of automated generated linear elements are generally of poor accuracy about especially gradient results. The proposed cell-based smoothed point interpolation method (CS-PIM) aims to improve the results accuracy of the thermoelastic problems via properly softening the overly-stiff stiffness. Design/methodology/approach This novel approach is based on the newly developed G space and weakened weak (w2) formulation, and of which shape functions are created using the point interpolation method and the cell-based gradient smoothing operation is conducted based on the linear triangular background cells. Findings Owing to the property of softened stiffness, the present method can generally achieve better accuracy and higher convergence results (especially for the temperature gradient and thermal stress solutions) than the FEM does by using the simplest linear triangular background cells, which has been examined by extensive numerical studies. Practical implications The CS-PIM is capable of producing more accurate results of temperature gradients as well as thermal stresses with the automated generated and unstructured background cells, which make it a better candidate for solving practical thermoelastic problems. Originality/value It is the first time that the novel CS-PIM was further developed for solving thermoelastic problems, which shows its tremendous potential for practical implications.


Designs ◽  
2021 ◽  
Vol 5 (1) ◽  
pp. 8
Author(s):  
Pyrrhon Amathes ◽  
Paul Christodoulides

Photography can be used for pleasure and art but can also be used in many disciplines of science, because it captures the details of the moment and can serve as a proving tool due to the information it preserves. During the period of the Apollo program (1969 to 1972), the National Aeronautics and Space Administration (NASA) successfully landed humans on the Moon and showed hundreds of photos to the world presenting the travel and landings. This paper uses computer simulations and geometry to examine the authenticity of one such photo, namely Apollo 17 photo GPN-2000-00113. In addition, a novel approach is employed by creating an experimental scene to illustrate details and provide measurements. The crucial factors on which the geometrical analysis relies are locked in the photograph and are: (a) the apparent position of the Earth relative to the illustrated flag and (b) the point to which the shadow of the astronaut taking the photo reaches, in relation to the flagpole. The analysis and experimental data show geometrical and time mismatches, proving that the photo is a composite.


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