Using autonomous intelligence to build a smart shop floor

Tang, Dunbing; Zheng, Kun; Zhang, Haitao; Zhang, Zequn; Sang, Zelei; Zhang, Tao; Espinosa-Oviedo, Javier A.; Vargas-Solar, Genoveva

doi:10.1007/s00170-017-0459-y

Cited by 24 publications

(10 citation statements)

References 27 publications

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“…Wang et al [91] described a system where an AGV was equipped with an RFID reader to read and write data to the products' RFID tags. Researchers have mentioned the role of mobile robots supplied with real-time data to perform material movement and internal transportation of parts and materials [13,74,87,90,[92][93][94]96,97,102]. Szafir et al [102] did experiments with drones to locate misplaced boxes in a warehouse environment.…”

Section: Category 1: Shopfloor Operational-related Activitiesmentioning

confidence: 99%

A Systematic Review on Technologies for Data-Driven Production Logistics: Their Role from a Holistic and Value Creation Perspective

2021

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A data-driven approach in production logistics is adopted as a response to challenges such as low visibility and system rigidity. One important step for such a transition is to identify the enabling technologies from a value-creating perspective. The existing corpus of literature has discussed the benefits and applications of smart technologies in overall manufacturing or logistics. However, there is limited discussion specifically on a production logistics level, from a systematic perspective. This paper addresses two issues in this respect by conducting a systematic literature review and analyzing 142 articles. First, it covers the gap in literature concerning mapping the application of these smart technologies to specific production logistic activities. Ten groups of technologies were identified and production logistics activities divided into three major categories. A quantitative share assessment of the technologies in production logistics activities was carried out. Second, the ultimate goal of implementing these technologies is to create business value. This is addressed in this research by presenting the “production logistics data lifecycle” and the importance of having a balanced holistic perspective in technology development. The result of this paper is beneficial to build a ground to transit towards a data-driven state by knowing the applications and use cases described in the literature for the identified technologies.

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Section: Category 1: Shopfloor Operational-related Activitiesmentioning

confidence: 99%

A Systematic Review on Technologies for Data-Driven Production Logistics: Their Role from a Holistic and Value Creation Perspective

2021

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“…Big data can help manufacturers to make more rational, responsive, and informed decisions, and enhance their competitiveness in the global market [47]. Moreover, intelligent shop floor should enable to sense dynamic manufacturing environment and agilely react to disturbances [48].…”

Section: Data-driven Dispatching Rule Mining and Decision-making Frameworkmentioning

confidence: 99%

“…A dispatching rule assigns the candidate jobs with highest priority firstly. It is often described as an algebraic expression in many literatures [48]. Take SPT rule as an example, SPT can be expressed as min pt or min (0.5 * pt + 0.5 * pt) algebraic expression, where, pt means processing time.…”

Section: Chromosome Representation and Decodingmentioning

confidence: 99%

Data-Driven Dispatching Rules Mining and Real-Time Decision-Making Methodology in Intelligent Manufacturing Shop Floor with Uncertainty

Zhang

Tang

et al. 2021

Sensors

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In modern manufacturing industry, the methods supporting real-time decision-making are the urgent requirement to response the uncertainty and complexity in intelligent production process. In this paper, a novel closed-loop scheduling framework is proposed to achieve real-time decision making by calling the appropriate data-driven dispatching rules at each rescheduling point. This framework contains four parts: offline training, online decision-making, data base and rules base. In the offline training part, the potential and appropriate dispatching rules with managers’ expectations are explored successfully by an improved gene expression program (IGEP) from the historical production data, not just the available or predictable information of the shop floor. In the online decision-making part, the intelligent shop floor will implement the scheduling scheme which is scheduled by the appropriate dispatching rules from rules base and store the production data into the data base. This approach is evaluated in a scenario of the intelligent job shop with random jobs arrival. Numerical experiments demonstrate that the proposed method outperformed the existing well-known single and combination dispatching rules or the discovered dispatching rules via metaheuristic algorithm in term of makespan, total flow time and tardiness.

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“…Kalor et al (2018) present methods of slicing deterministic and packet-switched industrial communication protocols which simplify the manageability of heterogeneous networks with various application requirements. Tang et al (2018) present an architecture of a smart shop floor based on physical, logical, and communication layers that embed intelligent approaches within manufacturing processes. Every physical entity on the smart shop floor is regarded as an autonomous intelligent logical unit that performs operations guided by distributed control functions.…”

Section: Communication In Industry 40 -Opc Uamentioning

confidence: 99%

Evaluation of OPC-UA communication in an autonomous advanced manufacturing cell implementation

et al. 2020

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The recent development of advanced manufacturing concepts brings new challenges for developing countries in order to prepare their workforce and industries for local and global markets. To explore and disseminate advanced manufacturing concepts, the first autonomous advanced manufacturing cell developed in Brazil as a result of a partnership between global and local companies and academia was designed and evaluated. This paper aims to describe the advanced manufacturing cell, the equipment composing the infrastructure, and the network topology and equipment that could deal with the heterogeneity of equipment and protocol. Moreover, the behavior of the Open Platform Communications Unified Architecture (OPC UA) communication framework (and related protocols) as the integration element between the equipment composing the cell was evaluated. The results indicated that the OPC UA communication framework promotes a low traffic overhead and can also be used to carry data from the traditional protocols in their fields without restrictions that could hinder production. The paper also discusses how the exchange of data occurred between the equipment used in the production and the control systems via the protocol studied. The OPC UA communication framework protocols presented a messaging structure and data transport characteristics that satisfy the integration needs between equipment of several manufacturers that composed an autonomous cell of advanced manufacturing. This paper also presents some key challenges to integrating all equipment not addressed by the OPC UA reference model.

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Using autonomous intelligence to build a smart shop floor

Cited by 24 publications

References 27 publications

A Systematic Review on Technologies for Data-Driven Production Logistics: Their Role from a Holistic and Value Creation Perspective

A Systematic Review on Technologies for Data-Driven Production Logistics: Their Role from a Holistic and Value Creation Perspective

Data-Driven Dispatching Rules Mining and Real-Time Decision-Making Methodology in Intelligent Manufacturing Shop Floor with Uncertainty

Evaluation of OPC-UA communication in an autonomous advanced manufacturing cell implementation

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