International Research Journal of Engineering and Technology (IRJET) Volume: 04 Issue: 03 | Mar -2017
www.irjet.net
e-ISSN: 2395 -0056 p-ISSN: 2395-0072
Criticality Analysis and Quality Appraisal of Innoson Injection Mould System C.C. Ihueze1, I.F., Ogbodo2.
1,2Department
of Industrial/Production Engineering, Nnamdi Azikiwe University, Awka, Anambra State, Nigeria
--------------------------------------------------------------****-------------------------------------------------------------ABSTRACT System reliability can be defined as the probability that a system will perform its intended function for a specified period of time under stated conditions (Ahmadi andSoderholm, 2008). It is important because a company’s reputation, customer satisfaction and system design costs can be directly related to the failures experienced by the system (Ansell and Phillip, 1994). It is also challenging since current estimation techniques require a high level of background in system reliability analysis, and thus familiarity with the system.
The current dynamic and turbulent manufacturing environment has forced companies that compete globally to change their traditional methods of conducting business. Recent developments in manufacturing and business operations have led to the adoption of preventive maintenance techniques that is based on systems and process that support global competitiveness. This paper employed Monte Carlo Normal distribution model which interacts with a developed Obudulu model to assess reliability and maintenance of Injection Moulding machine. The failure rate, reliability and standard deviations are reliability parameter used. Monte Carlo Normal distribution was used to analyse the reliability and failure rate of the entire system. The result shows that failure rate increases with running time accruing from wear due to poor lubrication systems; while system reliability decreases with increase time (years). Obudulu model was used to evaluate the variance ration of failure between system components under preventive maintenance and those outside preventive maintenance. The result shows that at reliability +0.3 and failure rate 0.02, preventive maintenance should be done. Interaction between the Monte Carlo normal distribution and obudulu model shows that the total system reliability is 0.489 when maintained which is 49% and 0.412 (41%) when not maintained. Also quality of production increased during Preventive maintenance while system downtime reduced greatly. These models were programmed using Monte Carlo Excel tool package software, showing the graphs of reliability and failure rates for each system.
Reliability represents safety level in industry practice and may variant due to time-variant operation condition and components deterioration throughout a product lifecycle (Billinton and Wang, 1999). Reliability remains a product quality indicator of paramount importance in competitive manufacturing operations. Offering novel ideas in enhancing product reliability levels is a subject of continuous research. Among the most popular approaches that aid in boosting reliability in manufactured products has been channelled through design of experiments (Blischke, Murthy, 2000). We use the concepts and methods of probability theory to compute the reliability of a complex system. In addition, we provide bounds on the probability of success that are often much easier to compute than the exact reliability (Ansell and Phillips, 1994). This is to identify the most likely failures and then identify appropriate actions to mitigate the effects of those failures.
Key words: Reliability, failure rates, Preventive maintenance, quality control and system downtime.
Injection molding is the most commonly used manufacturing process for the fabrication of plastic parts. A wide variety of products are manufactured using injection molding, which vary greatly in their size, complexity, and application. The injection molding process requires the use of an injection molding machine, raw plastic material, and a mold (Besseris, 2008).
1. INTRODUCTION Although the technological achievements of the last 50 years can hardly be disputed, there is one weakness in all mankind's devices. That is the possibility of failure. The introduction of every new device must be accompanied by provision for maintenance, repair parts, and protection against failure.
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Analysis of reliability of injection molding systems using Monte Carlo Simulation (MCS) method will provides very accurate values. Consequently, the method looks
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