Reliability evaluation and component importance measure for manufacturing systems based on failure losses

Abstract

Little work has been done to assess the reliability of a vital system like the manufacturing system. In this article, a novel and effective system reliability evaluation method in terms of failure losses has been proposed for manufacturing systems of job shop type, and then the failure losses based component importance measure (CIM) is used for importance analysis of equipment. The former indicates the present system reliability situation and the latter points the way to reliability improvement efforts. In this scheme, the problem is described and modeled by a dynamic directed network. Consider that the actual processing time of machines is to contribute to failure occurrence, it is used to calculate the failure times and failure losses. The obtained total failure times and failure losses of the system are applied to evaluate its reliability. Techniques to estimate two kinds of failure losses based CIMs are presented. They offer guidelines to realize system reliability growth cost-effectively. A case study of a real job shop is provided as an example to demonstrate the validity of the proposed methods. Comparison to other commonly used methods shows the efficiency of the proposed methods. CNCComputer numerical control DNC Distributed numerical control ERP Enterprise resource planning FT Failure times MES Manufacturing execution system MPT Machine processing time MTBF Mean time between failure MTTF Mean time to failure MTTR Mean time to repair OEE Overall equipment effectiveness RFID Radio frequency identification WDN Weighted and directed network WIP Work-in-process t, T Sequence number of time intervals (number of all intervals is T ) i, I t Sequence number of products items (number of all items is I t ) j, J t Sequence number of processes during t (J t is the maximum value) k, K Sequence number of equipment (number of all equipment is K ) G t WDN during t M k Equipment k r k Failure rate of M k F T tk Failure times of M k during t T total Total time V ti Volume size of item i during t B ti j Processing time of item i for the jth process during t x ti jk Be equal to 1 if M k is used for machining the jth process of item i during t, 0 otherwise MT B F k MTBF of M k MT T R k MTTR of M k C k Average maintenance cost for every repair process of M k 123 J Intell Manuf P L tk Production losses for M k during time period t C f k

A Multi-Criteria Decision Making Model for Ceramic Tiles Conveyor Selection

“…On the other hand, the reliability of the conveyor is decomposed into two subcriteria, namely, the failure rate and the repair or fixing speed. These measures are utilized in the assessment to reflect the most common reliability indices, namely, the mean time between failures (MTBF) and the mean time to repair (MTTR) [28].…”

Methodology of overall equipment effectiveness calculation in the context of Industry 4.0 environment

“…Ding [7] in their article describe a novel and effective system reliability evaluation method in terms of failure losses for manufacturing systems of job shop type, and then the failure losses based component importance measure (CIM) is used for importance analysis of equipment.…”

“…FT total (Total failure times) and FL total (Total failure losses) are novel and efficient reliability measures for job shop manufacturing system, and it is hard and improper to apply system MTBF to quantify the system reliability owing to the system attributes of multiple failure modes and multiple failure states. [7] The effective throughput, or the net throughput, also called OEE that is the number of conforming parts produced by the system in a given time. Grounding on this background knowledge, the production quality paradigm can be formulated in the following terms: Production quality is the discipline that combines quality, production logistics, and maintenance methods and tools to maintain the throughput and the service level of conforming parts under control and to improve them over time, with minimal waste of resources and materials [6,15,23].…”

Dynamic Importance Analysis of Components with Known Failure Contribution of Complex Systems

“…For example, the IM for complex systems with multiple components was proposed in [18]; Cadini et al [19] developed Monte-Carlo method for the analysis of systems with small failure probabilities. Zhang et al [20] proposed an approach to measure component importance of manufacturing systems based on failure losses. As an application example, a piston production line was chosen for evaluation purpose [21].…”