Towards flexible RFID event-driven integrated manufacturing for make-to-order production

Yao, Xifan; Zhang, Jianming; Li, Yongxiang; Zhang, Cunji

doi:10.1080/0951192x.2017.1407455

Cited by 21 publications

(15 citation statements)

References 42 publications

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“…Thus, event-based scheme can be more effective and economical considering the big data processing burden of time-based scheme [50]. Event-driven decision has shown many potential applications in manufacturing, such as manufacturing information system architecture [51], make-to-order production [52], and manufacturing execution system [53]. The most related research of event-based energy efficient production control is conducted by Li et al [30,54], where a sequence of disruption events was defined to estimate the production loss for energy saving operation.…”

Section: Methodology Of Event-driven Online Energy Saving Decision Anmentioning

confidence: 99%

Event-Driven Online Machine State Decision for Energy-Efficient Manufacturing System Based on Digital Twin Using Max-Plus Algebra

et al. 2019

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Energy-efficient manufacturing is an important aspect of sustainable development in current society. The rapid development of sensing technologies can collect real-time production data from shop floors, which provides more opportunities for making energy saving decisions about manufacturing systems. In this paper, a digital twin-based bidirectional operation framework is proposed to realize energy-efficient manufacturing systems. The data view, model view, and service view of a digital twin manufacturing system are formulated to describe the physical systems in virtual space, to perform simulation analysis, to make decisions, and to control the physical systems for various energy-saving purposes. For online energy-saving decisions about machines in serial manufacturing systems, an event-driven estimation method of an energy-saving window based on Max-plus Algebra is presented to put the target machine to sleep, considering real-time production data of a system segment. A practical, simplified automotive production line is used to illustrate the effectiveness of the proposed method by simulation experiments. Our method has no restriction on machine failure mode and predefined parameters for energy-saving decision of machines. The proposed approach has potential use in synchronous and asynchronous manufacturing systems.

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Section: Methodology Of Event-driven Online Energy Saving Decision Anmentioning

confidence: 99%

Event-Driven Online Machine State Decision for Energy-Efficient Manufacturing System Based on Digital Twin Using Max-Plus Algebra

et al. 2019

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“…With rising quality standards and greater product liability, traceability is becoming increasingly important in the manufacturing industry for tracking individual parts, subassemblies and products in real time throughout the manufacturing process, from raw materials entering the factory to final products being delivered to the customer. It can provide manufacturers with real-time visibility into their operations to facilitate root-cause analysis and continuous improvement of quality and efficiency (Yao et al, 2018). In addition, using traceability technologies (e.g.…”

Section: Vertical Integrationmentioning

confidence: 99%

“…Additive manufacturing also can improve manufacturing flexibility, allowing manufacturers to respond to changing requirements in uncertain and competitive global markets (Yao et al, 2018). In contrast to conventional manufacturing approaches that remove material from a stock item, additive manufacturing produces a three-dimensional-shaped structure by successively adding material layer by layer from a computer-aided design model.…”

Section: Vertical Integrationmentioning

confidence: 99%

“…In contrast to conventional manufacturing approaches that remove material from a stock item, additive manufacturing produces a three-dimensional-shaped structure by successively adding material layer by layer from a computer-aided design model. It can enhance flexibility by (1) manufacturing products "on-demand" for low volume production in response to customer orders, (2) producing parts with complex geometries, (3) fabricating parts without tooling, (4) exploiting process variables for efficient production and (5) producing tools or molds for subtractive processes (Yao et al, 2018). Several additive manufacturing methods have been developed, such as powder bed fusion and material extrusion (topics 11 and 12).…”

Section: Vertical Integrationmentioning

confidence: 99%

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A topic-based patent analytics approach for exploring technological trends in smart manufacturing

Wang

Hsu

2020

JMTM

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PurposeSmart manufacturing can lead to disruptive changes in production technologies and business models in the manufacturing industry. This paper aims to identify technological topics in smart manufacturing by using patent data, investigating technological trends and exploring potential opportunities.Design/methodology/approachThe latent Dirichlet allocation (LDA) topic modeling technique was used to extract latent technological topics, and the generalized linear mixed model (GLMM) was used to analyze the relative emergence levels of the topics. Topic value and topic competitive analyses were developed to evaluate each topic's potential value and identify technological positions of competing firms, respectively.FindingsA total of 14 topics were extracted from the collected patent data and several fast growth and high-value topics were identified, such as smart connection, cyber-physical systems (CPSs), manufacturing data analytics and powder bed fusion additive manufacturing. Several leading firms apply broad R&D emphasis across a variety of technological topics, while others focus on a few technological topics.Practical implicationsThe developed methodology can help firms identify important technological topics in smart manufacturing for making their R&D investment decisions. Firms can select appropriate technology strategies depending on the topic's emergence position in the topic strategy matrix.Originality/valuePrevious research studies have not analyzed the maturity levels of technological topics. The topic-based patent analytics approach can complement previous studies. In addition, this study provides a multi-valuation framework for exploring technological opportunities, thus providing valuable information that supports a more robust understanding of the technology landscape of smart manufacturing.

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“…developed an RFIDenabled social manufacturing system to realize the real-time monitoring and dispatching of inter-enterprise production and transportation tasks. Yao et al (2018) proposed an RFID event-driven integrated production planning and control framework for such a need in a make-to-order service-oriented architecture-based production environment. To solve the increasing production data that are sometimes discrete, uncorrelated and hard-to-use, provided an RFID-based production data analysis method for production control in Internet-of-Things-enabled smart jobshops.…”

Section: Production Tracking and Monitoring In Laborintensive Manufacturing Enterprisesmentioning

confidence: 99%

RFID-based tracking and monitoring approach of real-time data in production workshop

et al. 2019

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Purpose In practical workshop production process, there are many production emergencies, e.g. new manufacturing tasks, facilities failure and tasks change. On one hand, it results in poor timeliness and reliability of real-time production data collection, acquisition and transmission; on the other hand, it increases the difficulty of real-time data tracking and monitoring. This paper aims to develop a novel RFID-based tracking and monitoring approach of real-time data in production workshop (TMrfid) to solve them. Design/methodology/approach At first, a three-layer model of real-time data based on RFID has been constructed, which contains RFID-based integrated acquisition center; “RFID & Cloud-service-rules”-based calculation and analysis center; and “RFID & Ontology-knowledge-base”-based monitoring and scheduling center. Then, a targeted analysis and evaluation method of TMrfid with feasibility, quality and performance has been proposed. Finally, a prototype platform of a textile machinery manufacturing enterprise has been built to verify the effective of TMrfid. Findings The effectiveness of TMrfid is verified by applying two groups of actual experimental data from the case enterprise, the results show that TMrfid can promote the efficiency, reliability and feasibility of tacking and monitoring of real-time data in production workshop. Originality/value RFID-based tracking and monitoring approach of real-time data in production workshop has been developed to solve the data information transmission and sharing problem. Three analysis and evaluation approaches have been introduced to solve the un-standardized evaluation problem of RFID application. A prototype platform of a textile machinery manufacturing enterprise has been constructed.

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Towards flexible RFID event-driven integrated manufacturing for make-to-order production

Cited by 21 publications

References 42 publications

Event-Driven Online Machine State Decision for Energy-Efficient Manufacturing System Based on Digital Twin Using Max-Plus Algebra

Event-Driven Online Machine State Decision for Energy-Efficient Manufacturing System Based on Digital Twin Using Max-Plus Algebra

A topic-based patent analytics approach for exploring technological trends in smart manufacturing

RFID-based tracking and monitoring approach of real-time data in production workshop

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