A performance evaluation method for radio frequency identification–based tracking network of job-shop-type work-in-process material flows

Zhang, Fuqiang; Jiang, Pingyu; Zheng, Mingbo; Cao, Wei

doi:10.1177/0954405413481713

Cited by 15 publications

(7 citation statements)

References 25 publications

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“…Jiang developed an enhanced radio frequency identification (RFID)-enabled graphical deduction model (rfid-GDM) for tracking the time-sensitive state, position, and other attributes of RFID-tagged objects in process flow [18]. Zhang constructed a job-shop-type work-in-process material flows tracking network, and some new metrics were presented to evaluate the work-in-process material flows tracking network performance [19]. It can be seen that the essence of process logistics monitoring is how to effectively identify different states changes of perceived by RFID devices.…”

Section: Brief Reviewmentioning

confidence: 99%

“…(3) Suppose that the column IDs corresponding to two elements that are recorded in chronological order in i th row of matrix W B(t) are g and h. The transport time WCT (i, g, h) from completed processing in processing unit U g to transport to next processing unit U h can be calculated by (19):…”

Section: Out/in Warehouse Information Analysismentioning

confidence: 99%

“…The negative element in matrix W B T (25) denotes that the job has not been machined in the corresponding processing unit; the zero element in matrix W M T (25) denotes that the job has not been processed at the corresponding processing unit, and the negative element denotes that the job has not been machined in the corresponding processing unit at this time; the transportation time of job can be calculated by (19) and (20), as shown in Table 2.…”

Section: Construct the Process Logistics State Matricesmentioning

confidence: 99%

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An RFID Data Matrices‐Based Evaluation Method for Process Logistics State

Feng

Han

Zhang

et al. 2019

Mathematical Problems in Engineering

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At present, radio frequency identification (RFID) technology has been widely applied in manufacturing industry. How to use collected RFID data to effectively evaluate process logistics state is an urgent problem. Firstly, process logistics state model based on extended disjunctive graph was established. Secondly, configuration scheme of RFID readers/tags and production elements was proposed according to the time and space characteristics of process logistics. Then, process logistics state matrices including jobs, warehouses, buffers, machine tools, and vehicles were constructed. The real-time process logistics states can be deduced by operation of above data matrices. Finally, a case study was proposed to verify the feasibility of the proposed methods.

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Section: Brief Reviewmentioning

confidence: 99%

Section: Out/in Warehouse Information Analysismentioning

confidence: 99%

Section: Construct the Process Logistics State Matricesmentioning

confidence: 99%

See 1 more Smart Citation

An RFID Data Matrices‐Based Evaluation Method for Process Logistics State

Feng

Han

Zhang

et al. 2019

Mathematical Problems in Engineering

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“…In terms of workers, machines and materials, the efficiency and effectiveness of the proposed RT-MES are evaluated for shop floor production management. Zhang et al 20 propose a performance evaluation method for RFID-based tracking network of job-shop-type work-in-process (WIP) material flows. It is expected that their study will provide a systemic evaluation method for guiding and optimizing the RFID-based tracking configuration solution.…”

Section: Literature Reviewmentioning

confidence: 99%

Radio frequency identification–enabled monitoring and evaluating in the discrete manufacturing process

Yuan

Guo

Wei

et al. 2016

Proceedings of the Institution of Mechanical Engineers, Part B:

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Process monitoring is a major focus on improving productivity of discrete manufacturing. With the recent application of new technologies such as radio frequency identification to manufacturing process, real-time production information has become available for decision support in manufacturing system. This study presents a radio frequency identification–based visibility monitoring rule for tracking work-in-process. Specific to the aviation manufacturing shop floor, a case study for demonstration is designed. The value of radio frequency identification–enabled real-time information is investigated within the discrete manufacturing operation. For this purpose, a simplified simulation model is developed to test the benefit of radio frequency identification–based rule compared to the classical scheduling rule. The results indicate that the adoption of radio frequency identification brings better production performance.

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“…Vrabič et al (2013) proposed a network model used for anomaly detection. A radio frequency identification-based tracking network is established to track the material flows in a job-shop floor (Zhang et al 2013). Enterprises are treated as nodes in production networks and supply chain networks at inter-enterprise level (Hiremath et al 2013;Papakostas et al 2012), but they are not emphases of this paper.…”

Section: Reliability Analysis Of Systems With Network Structuresmentioning

confidence: 99%

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

Zhang

et al. 2015

J Intell Manuf

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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

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A performance evaluation method for radio frequency identification–based tracking network of job-shop-type work-in-process material flows

Cited by 15 publications

References 25 publications

An RFID Data Matrices‐Based Evaluation Method for Process Logistics State

An RFID Data Matrices‐Based Evaluation Method for Process Logistics State

Radio frequency identification–enabled monitoring and evaluating in the discrete manufacturing process

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

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