scholarly journals A Costing Analysis for Decision Making Grid Model in Failure-Based Maintenance

2011 ◽  
Vol 2011 ◽  
pp. 1-15 ◽  
Author(s):  
Burhanuddin M. A. ◽  
Sami M. Halawani ◽  
A. R. Ahmad
Keyword(s):  
Decision Making ◽  
Production Cost ◽  
Good Control ◽  
Fish Bone ◽  
Maintenance Cost ◽  
Economic Downturn ◽  
Repair Cost ◽  
Grid Model ◽  
Computerized Maintenance Management System ◽  
Costing Analysis

Background. In current economic downturn, industries have to set good control on production cost, to maintain their profit margin. Maintenance department as an imperative unit in industries should attain all maintenance data, process information instantaneously, and subsequently transform it into a useful decision. Then act on the alternative to reduce production cost. Decision Making Grid model is used to identify strategies for maintenance decision. However, the model has limitation as it consider two factors only, that is, downtime and frequency of failures. We consider third factor, cost, in this study for failure-based maintenance. The objective of this paper is to introduce the formulae to estimate maintenance cost. Methods. Fish bone analysis conducted with Ishikawa model and Decision Making Grid methods are used in this study to reveal some underlying risk factors that delay failure-based maintenance. The goal of the study is to estimate the risk factor that is, repair cost to fit in the Decision Making Grid model. Decision Making grid model consider two variables, frequency of failure and downtime in the analysis. This paper introduces third variable, repair cost for Decision Making Grid model. This approaches give better result to categorize the machines, reduce cost, and boost the earning for the manufacturing plant. Results. We collected data from one of the food processing factories in Malaysia. From our empirical result, Machine C, Machine D, Machine F, and Machine I must be in the Decision Making Grid model even though their frequency of failures and downtime are less than Machine B and Machine N, based on the costing analysis. The case study and experimental results show that the cost analysis in Decision Making Grid model gives more promising strategies in failure-based maintenance. Conclusions. The improvement of Decision Making Grid model for decision analysis with costing analysis is our contribution in this paper for computerized maintenance management system.

scholarly journals Forecasting Machine Failure Using DMG and Weibull Analysis in an Automotive Industry: A Case Study

2021 ◽  
Vol 40 (2) ◽  
pp. 435-442
Author(s):  
Kamran Shah ◽  
Hassan Khurshid ◽  
Izhar Ul Haq ◽  
Shaukat Ali Shah ◽  
Zeeshan Ali
Keyword(s):  
Decision Making ◽  
Manufacturing Industry ◽  
Management Strategies ◽  
Fixed Time ◽  
Maintenance Management ◽  
Maintenance Cost ◽  
Weibull Analysis ◽  
Effect Analysis ◽  
Machine Failure ◽  
Computerized Maintenance Management System

In manufacturing or production setup, maintenance cost is one of the major portions of overall operating expenditure. It can vary between 15 to 60 percentage of overall cost for various industries including food related industries, iron, steel and other heavy industries. Such a high cost directly impacts manufacturing setup, profitability and sustainability in long run. In most of the industries, ineffective maintenance management can result in loss of capital and inefficient human resource deployment. This in turn affects the plants’ ability to manufacture quality products that are competitive in the market. Various maintenance management strategies including Operate to Failure (OTF), Design Out Maintenance (DOM), Skill Level Upgrade (SLU), ConditionBased Monitoring (CBM) and Fixed Time Maintenance (FTM) are used in industries for maximizing productivity. In recent years, Computerized Maintenance Management System (CMMS) has become an integral part of most of the industries so its importance and characteristics cannot be understated. While CMMS cannot live standalone, it requires some decision-making techniques to be equipped with. These techniques range from Failure Mode and Effect Analysis (FMEA) to Decision Making Grid (DMG). In this paper, concept of DMG has been applied to an automotive parts Manufacturing Industry in conjunction with Weibull analysis. Parallels are drawn between the results of DMG and Weibull analysis.

Optimization of equal-cycle maintenance strategy considering imperfect preventive maintenance

2021 ◽  
pp. 095440892110638
Author(s):  
Xinlong Li ◽  
Yan Ran ◽  
Genbao Zhang
Keyword(s):  
Decision Making ◽  
Preventive Maintenance ◽  
Maintenance Cost ◽  
Maintenance Strategy ◽  
Action Unit ◽  
Cost Rate ◽  
Equipment Reliability ◽  
Optimal Maintenance ◽  
Important Means ◽  
Maintenance Decision

Preventive maintenance is an important means to extend equipment life and improve equipment reliability. Traditional preventive maintenance decision-making is often based on components or the entire system, the granularity is too large and the decision-making is not accurate enough. The meta-action unit is more refined than the component or system, so the maintenance decision-making based on the meta-action unit is more accurate. Therefore, this paper takes the meta-action unit as the research carrier, considers the imperfect preventive maintenance, based on the hybrid hazard rate model, established the imperfect preventive maintenance optimization model of the meta-action unit, and the optimization solution algorithm was given for the maintenance strategy. Finally, through numerical analysis, the validity of the model is verified, and the influence of different maintenance costs on the optimal maintenance strategy and optimal maintenance cost rate is analyzed.

Two-stage flexible warranty decision-making considering downtime loss

2019 ◽  
Vol 234 (3) ◽  
pp. 527-535
Author(s):  
Rui Zheng ◽  
Chun Su ◽  
Yuqiao Zheng
Keyword(s):  
Decision Making ◽  
Preventive Maintenance ◽  
Maintenance Cost ◽  
Service Cost ◽  
Decision Framework ◽  
Two Stage ◽  
Warranty Period ◽  
Second Stage ◽  
Warranty Service ◽  
Warranty Policies

Most existing warranty policies are rigid, and the downtime loss is also not taken into account. This study develops a two-stage decision framework to design flexible warranty policies, where the downtime loss is considered. In the first stage, by minimizing the warranty service cost, a fixed warranty policy is provided to determine the baseline of preventive maintenance’s times and effort. In the second stage, customers have three options to increase preventive maintenance times, preventive maintenance effort, or both of them, which results in three types of flexible warranty policies. The additional maintenance cost for the increased preventive maintenance times and/or preventive maintenance effort is paid by the customers. Besides, the flexible policies are optimized to minimize customer’s cost, which is the sum of the downtime loss and shared maintenance cost. A practical example is provided to illustrate the effectiveness of the proposed flexible warranty policies. The results indicate that compared with the fixed warranty policies, both the manufacturer and customers can benefit from the proposed flexible policies, especially when the downtime loss is substantial. Moreover, the proposed policy is more effective when the warranty period is longer.

Water pollution control in the river basin by fuzzy genetic algorithm-based multiobjective programming modeling

1998 ◽  
Vol 37 (8) ◽  
pp. 55-63 ◽  
Author(s):  
H. W. Chen ◽  
Ni-Bin Chang
Keyword(s):  
Genetic Algorithm ◽  
Water Quality ◽  
Decision Making ◽  
River Basin ◽  
Control Strategies ◽  
Water Quality Management ◽  
Good Control ◽  
Optimization Techniques ◽  
Water Quality Control ◽  
Fuzzy Genetic

Designing water quality management strategies is often complicated by the difficulty in simultaneously considering large amounts of relevant data, applicable submodels, competing objectives, unquantifiable factors, nonlinear characteristics, and uncertainty during parameterization. Mathematical optimization techniques offer promise in identifying optimal or satisfactory strategies that may be used as benchmarks for decision making. Newer optimization techniques such as genetic algorithm (GA) and fuzzy mathematical programming make the search for optimal control strategies in an uncertain environment more feasible. Using a probabilistic search procedure that emulates Darwinian natural selection, GAs allow multicriteria decision making with respect to both nonlinear feature and fuzzy characteristics to be incorporated directly into the optimization process and generate trade-off curves between cost and environmental quality while identifying good control strategies. This paper verifies such a discovery by a case study of water quality control in the Tseng-Wen river basin in Taiwan.

A STOCHASTIC MODEL FOR TRI-PARTITE SERVICE CONTRACTS

2013 ◽  
Vol 20 (02) ◽  
pp. 1350010 ◽  
Author(s):  
N. SHAMSI GAMCHI ◽  
M. ESMAEILI ◽  
M. A. SANIEE MONFARED
Keyword(s):  
Maintenance Cost ◽  
Repair Cost ◽  
Sale Price ◽  
Numerical Examples ◽  
Service Contract ◽  
Penalty Cost ◽  
Warranty Period ◽  
Service Contracts ◽  
Optimal Maintenance ◽  
First Time

Warranty as a kind of service contract plays a key role in business and legal transactions today. In this paper, we present for the first time a tri-partite service contract model including a manufacturer, an agent and a customer under risk parameter. We determine an optimal sale price, a warranty period and a warranty price for the manufacturer under quantity discount policies. The optimal maintenance cost or repair cost is obtained by the maximizing of an agent's profit according to the penalty cost incurred due to waiting time. Moreover, the customer maximizes his/her satisfaction by purchasing several products and choosing a portfolio of service contracts. Whereas the risk-aversion parameter on the customer side has an impact on their decision for choosing the type of service contract. On the other hand, the discount rate regime on the manufacturer side influences the number of purchased products. We present some numerical examples to illustrate the working logic of our model.

scholarly journals The Effect Of The Economic Downturn On The Way People Travel For Leisure And For Business: The Case Of Spain

2015 ◽  
Vol 19 (2) ◽  
pp. 95
Author(s):  
Ramon Diaz-Bernardo
Keyword(s):  
Decision Making ◽  
Travel Behavior ◽  
Future Research ◽  
Economic Downturn ◽  
Business Travelers ◽  
Leisure Travelers ◽  
Travel Decision ◽  
The Way ◽  
Decision Making Criteria

This study contributed to existing literature by investigating how business and leisure travelers make travel-related decisions. By developing scales to measure travel behavior and travel decision-making criteria, this study contributes to the literature on business travelers vs. leisure travelers. Finally, this study proves a convergence in the behavior of business travelers vs. leisure travelers, in their motivations and decision-making criteria, and provides possible explanations for this trend and avenues for potential future research lines.

scholarly journals A decision support approach to achieve competitive advantage for a hypermarket chain

2021 ◽  
Author(s):  
Aapo Siljamäki
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Competitive Advantage ◽  
Support System ◽  
Development Process ◽  
Background Information ◽  
Economic Downturn ◽  
Observation Matrix ◽  
Shopping Basket

AbstractThis paper describes the decision support approach used in the development process of the S Group's Prisma hypermarket chain in Finland. The management was looking for a new and sustainable operating model for the rapidly growing chain, and contacted the author to consult in the process. Fierce competition forced the search for new business ideas, tools and methods that would provide a clear competitive advantage. To find new perspectives, we decided to use statistical approaches and various decision support system options, such as multi-criteria modelling. A database was available for research and analysis, including data on purchasing behavior and key performance indicators (KPI). The approach had to take into account the role and impact of customers. It was highly important to include customer behavior in the analysis using shopping basket data. Shopping basket data was central in the current paper. From these, an observation matrix was created combining shopping basket data, product data and customer background information. Using multivariate methods, customer groupings and profiles were created with the data from the observation matrix. Using the customer profile and KPI data, a multi-criteria decision support system was produced to support strategic planning. The decision support system (DSS) model was created together with a market chain operational expert and an external methodological expert. We used the VIG software package developed by Korhonen (Belg J Oper Res Stat Comput Sci 27(3):15, 1987) to solve the problem because it is easy to use and requires no prior knowledge of computers or multi-objective linear programming models. Pareto Race plays a central role in the VIG system. The chain expert easily learned how to use and work with the model. The results were immediately visible and could be used to examine alternatives and assess their appropriateness. It was decided to present five different scenarios to the hypermarket chain management. The main objective of the development process was to develop a strategy that would provide the Prisma hypermarket chain with a long-term competitive advantage. Various models were developed and used to support the strategy work by analysing and exploring the data collected, prioritising and selecting decision options. Two currently retired managers (Mönkkönen, S Group, the chain manager, Prisma chain, Interview 02.06.2021, 2021), who were involved in the development process, rated the strategy process as very successful and the modelling carried out during the process significantly supported decision-making. The immediate help of DSS modelling for decision making comes from being able to provide decision makers with reasonable, better solution options to support their decision making. The final impact of decisions could be evaluated after a longer period of time, which in the case of the Prisma development project results means several comparable financial years. Finland suffered exceptionally badly from the financial crisis and the global economic downturn in 2008–2009. The Prisma chain has survived the periods and crises described above without any loss-making years, and the whole chain has grown from 16 units in 1992 to 68 units in 2020.

Sign in / Sign up

Export Citation Format

Share Document