Information Links between Product Life Cycles and Production System Management in Designing of Digital Manufacturing

Kutin, Andrey; Долгов, В. А.; Sedykh, Mikhail

doi:10.1016/j.procir.2015.12.126

Cited by 23 publications

(13 citation statements)

References 6 publications

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“…(2) Production quality The production quality of all machines in the digital production control system is described by a production quality matrix Ve = (vij)n e ×l e , where vij is the production quality of the j th subtask on the i th machine. According to the production process and precision, vij can be divided into six levels: B = [0, 2,4,6,8,10].…”

Section: Collaborative Allocation Of Sub-tasksmentioning

confidence: 99%

“…In the past two decades, China has achieved a rapid progress of manufacturing. But there is still a large gap from the advanced level of manufacturing in developed countries [1][2][3][4][5][6][7]. Since the proposal of the China Manufacturing 2025 strategy, the penetration of Internet of Things (IoT) in the production control of modern manufacturing workshop has prompted advanced intelligent and information-based manufacturing techniques, such as manufacturing logistics [8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

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Digital Production Control of Manufacturing Workshop Based on Internet of Things

Wang¹,

Li²,

Nie³

2021

Int. j. simul. model.

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The penetration of Internet of things (IoT) in the production control of modern manufacturing workshop has prompted advanced intelligent and information-based manufacturing techniques. However, the relevant studies fail to collect and process the various manufacturing parameters in real time, and rarely consider the coordination between manufacturing workshop and machines. This paper explores the digital production control of manufacturing workshop based on the IoT. Firstly, block diagrams were drawn for IoT-based digital workshop production control and software design of digital production control system, and a multi-objective optimization model was established for IoT-based digital workshop production control, aiming to optimize delivery time, machine load, and machine utilization rate. Next, the order sequencing method was detailed for digital workshop production control. Finally, machine competency and collaborative efficiency were introduced as optimization objectives, and an IoT-based strategy was designed for collaborative allocation of sub-tasks for workshop production. Our method was proved effective through experiments.

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Section: Collaborative Allocation Of Sub-tasksmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Digital Production Control of Manufacturing Workshop Based on Internet of Things

Wang¹,

Li²,

Nie³

2021

Int. j. simul. model.

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“…• repairs of equipment by operating time. Accounting for the above factors in operational scheduling systems is usually not carried out, but during production, these factors can have a significant impact on the implementation of the production plan [6][7][8].…”

Section: Research Of Functional Capabilities and Determination Of Thementioning

confidence: 99%

“…However, such systems do not allow us to take into account a number of factors, including probabilistic ones, which are typical for any real production, such as equipment failures, repairs, transport restrictions, and others. At the same time, such factors can have a decisive impact on the timing and ability to complete a given production plan [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

PlantTwin simulation system as a tool for verifying production plans and supporting decision-making to improve the efficiency of machine-building industries

Nikishechkin¹,

Ivashin²,

Chernenko³

et al. 2020

MATEC Web Conf.

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The article deals with the issues of improving the efficiency of production and logistics systems (PLS) of machine-building enterprises through the joint use of MES/APS systems and simulation systems for verification of production plans and decision support. The possibility of using the PlantTwin simulation system on the example of a small machine- building enterprise is considered. Simulation of the operation of the enterprise’s PLS when performing a given production program is performed. Based on the results of simulation modeling, a number of organizational and technological proposals and recommendations for improving the efficiency of the enterprise’s PLS were formed. The proposed solutions were verified by making changes to the simulation scenario and obtaining new results showing their effectiveness.

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“…The effectiveness of any production, including the "digital", largely depends on the effectiveness of technological planning of production [4]. One of the important directions in the process planning is the identification of models of technological equipment, its quantity and uniform loading for the fulfillment of a given program of production.…”

Section: Introductionmentioning

confidence: 99%

Method of workpiece grouprs creation and selection of parts representatives in digital manufacturing

Kutin¹,

Sedykh²,

Ivashin³

2018

Proceedings of the International Conference "Actual Issues of Mechanical Engineering" (AIME 2018)

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For modern high-efficiency digital production, the main requirement is its ability at any time to break evenly the manufacture of products and in a short time with minimal costs to start producing any number of new products. The fulfillment of this task largely depends on the efficiency of the technological planning of production, which makes it possible to integrate the manufacturing of a new product into existing technological processes at a minimal time to market with the minimum costs using available technological equipment, fixtures, tools, etc. When developing new products, engineers are trying to design parts similar to those already developed and manufactured at the enterprise, but this does not always work. In addition, there are questions concerning determining the load of equipment when introducing new products. All these issues in manufacturing help to solve the methods of bringing the release program. This article presents a technique for splitting the multinomenclature machine-building production into groups of parts, selecting the details-representatives, calculating the manufacturing times for the details of the above-mentioned output program, and comparing the times obtained by calculation with the processing times of the workpieces on the machines by the example of manufacturing the "Transition plate" parts.

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Information Links between Product Life Cycles and Production System Management in Designing of Digital Manufacturing

Cited by 23 publications

References 6 publications

Digital Production Control of Manufacturing Workshop Based on Internet of Things

Digital Production Control of Manufacturing Workshop Based on Internet of Things

PlantTwin simulation system as a tool for verifying production plans and supporting decision-making to improve the efficiency of machine-building industries

Method of workpiece grouprs creation and selection of parts representatives in digital manufacturing

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