Job Shop Scheduling Based on Digital Twin Technology: A Survey and an Intelligent Platform

Abstract

The concept of digital twinning has become a hot topic in the manufacturing industry in recent years. The emerging digital twin technology is an intelligent technology that makes full use of multimodels, big data, and interdisciplinary knowledge, which provides some new approaches for the field of the intelligent manufacturing industry. The job shop scheduling problem has been an important research field in the discrete manufacturing industry. Digital twin technology is adopted to solve the problem of job shop scheduling, which provides the possibility for the intelligent development of workshops. Based on digital twin technology and combined with the actual problem of production line scheduling, we propose a new intelligent scheduling platform to solve the shop scheduling problems above. Meanwhile, based on the prediction and diagnosis of multisource dynamic interference in the workshop production process by big data analysis technology, the corresponding interference strategy is formulated in advance by the scheduling cloud platform. The model simulation experiment of intelligent dispatching cloud platform was carried out, and some enterprises in intelligent manufacturing workshop were taken as examples to verify the superiority of the dispatching cloud platform. Finally, we look forward to the future research direction of intelligent manufacturing based on digital twin technology.

An Imitation and Heuristic Method for Scheduling with Subcontracted Resources

“…To date, some methods to solve the scheduling problem with resource constraints have been developed depending on the problem statement, restrictions, and objective function. These are scheduling theory and network methods [1][2][3][4][5], simulation and multi-agent modelling methods [6,7], heuristic methods [8,9], and methods based on the application of commercially available solvers [10][11][12][13][14].…”

“…According to the machine environment, scheduling problems can be divided into the main following types with the type notation in brackets [15]: identical parallel machines (Pm) where work can be performed at any of the machines [1][2][3][4][5]8,9,12,14]; Job shop (Jm) where each work has to be processed on each of the machines and all works have different routes [6,7,11,13]; Open shop (Om) where each work has to be processed on each of the machines and some of this processing time may be zero [10].…”

“…According to the processing restrictions, there are several main constraints specified: release dates (r j ), where work j cannot start its processing before its release date [3][4][5]; precedence constraints (prec), where one or more works have to be completed before execution of a certain consequent work is allowed [1][2][3][4][5][6][7][8][9][12][13][14]; batch processing (batch(b)), where a machine may be able to process a number of b works simultaneously [11,12]; and breakdowns (brkdwn), where a machine may not be permanently available [3,5].…”

“…Mathematics 2021, 9, 2098 2 of 22 and the weighted number of tardy jobs minimization (∑ ω j U j ) [5,[11][12][13][14], throughput maximization [10].…”

“…Examples of the renewable resources are personnel, aggregates, vehicles, and other. At the same time, there is an urgent problem to consider non-renewable resources' distribution, as in [3,7,13]. The non-renewable resources are consumed at the work input and produced at the work output.…”