Forecasting Machine Failure Using DMG and Weibull Analysis in an Automotive Industry: A Case Study
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), Condition Based 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.