Architecture Of Manufacturing Execution System Research Articles

SaaMES: SaaS-Based MSA/MTA Model for Real-Time Control of IoT Edge Devices in Digital Manufacturing

As a software delivery model, Software as a Service (SaaS) has attracted considerable attention from software providers and users. Most traditional companies are shifting their businesses to an SaaS model. SaaS development is a very complicated process and its success depends on architectural design and development. A Manufacturing Execution System (MES) was used at the expense of licensing fees for features not used in the On-Premise environment, although the features used vary depending on the manufacturing environment. In an SaaS environment, MES is applied with a function-specific container approach through a Microservice Architecture (MSA) to select and employ only the necessary functions. Furthermore, as the number of customers of virtualized applications increases in SaaS-based services, complexity and operating costs increase; thus, Multi-tenancy Architecture (MTA) technology, which serves all customers through a single instance of the application is crucial. Thus, in this study, we investigate the MTA approach and propose a suitable MTA for the manufacturing execution system. Real-time response is crucial to achieving a cyber-physical system of digital manufacturing in SaaS-based MES. Furthermore, SaaS-based big data analytics and decision-making cannot meet the needs of numerous applications in real-time sensitive workplaces. In this study, we propose an SaaS-based MSA/MTA model for real-time control of Internet of Things (IoT) Edge in digital manufacturing (SaaMES), an architecture of SaaS-based MES with MSA and MTA to meet vulnerable workplaces and real-time responses in Cloud environments. The analysis is used by applying the Autoencoder and Generic Adversarial Networks analysis model to IoT Edge for the connection between the Cloud environment and work site to enable real-time response and decision-making through communication using OPC-UA and small-scale analysis.

Cloud-based architecture of service-oriented MES for subcontracting and partnership exchanges integration: A game theory approach

• An agile cloud-based architecture for integrating ERP, MES and SPX. • Optimal selection of main contractor and subcontractor based on game theory. • Providing distributed production inside distributed enterprises. • Distribution of required services in an intelligent mode. Subcontracting and Partnership Exchanges (SPXs) have been developed to increase networking among Small and Medium Enterprises (SMEs) and large enterprises. SPXs provide technical information centers, advanced mechanisms and matchmaking between main contractors, suppliers and subcontractors. In general, Enterprise Resource Planning (ERP) and Manufacturing Execution System (MES) have not adequate efficiency to solve the required enterprise's goals. Thus, this study proposed an agile cloud-based architecture of ERP, MES and SPX integration. This architecture supports distributed enterprises. The amazing points of the mentioned architecture abilities are the optimal selection of main contractors and subcontractors based on game theory approach. The main contractor and subcontractor selection decision in SPX center are modeled using the dynamic, sequential and noncooperative game model. The Nash equilibrium of the proposed game provides an optimized payoff function for different players against the combination of their strategies. The results show the architecture can present the distribution of required services in an intelligent mode. Also, the enabler factors such as cost, rapid elasticity, quality, response and so on have been considered to agility validation of this new architecture.

Visualized Modeling and Simulation of Manufacturing Execution System in Dynamic Job-Shop Scheduling

Manufacturing Execution System (MES) is a job-shop production oriented management information system and the bridge between production plan management layer and job-shop control layer in an enterprise. Job-shop scheduling is the core module of MES, which direct affects the efficiency of production and management in the enterprise. According to the characteristics of discrete production management, a job-shop production scheduling system is presented that adapts to multi-variety small-batch production. A MES architecture for dynamic discrete production and its core modules are presented. Then, dynamic job-shop production scheduling problem is visually modeled and simulated based on Witness to realize optimal resource deployment.

MES (manufacturing execution system) architecture for FMS compatible to ERP (enterprise planning system)

Presented in the paper is MES (manufacturing execution system) architecture, which is suitable for managing FMS (flexible manufacturing system) lines under an ERP (enterprise planning system)environment. An IDEF0-model of an 'order handling' shop floor having an FMS line is developed to identify functional requirements of MES, and then a two-tier MES architecture satisfying the functional requirements is proposed. The proposed MES is composed of a Main-MES (for the main shop floor) and an FMS-MES (for the FMS line). A BOP (bill of processes) is used as a means to represent process plans, and a LS-Net (loading schedule network) is used as a mechanism for representing and manipulating loading schedules. Object models of BOP and LS-Net are presented, and the effectiveness of the proposed MES is demonstrated by applying it to two FMS lines, a stamping-die machining line and a mechanical part machining line.