Generic platform for manufacturing execution system functions in knowledge-driven manufacturing systems

Mohammed, Wael M.; Ferrer, Borja Ramis; Iarovyi, Sergii; Negri, Elisa; Fumagalli, Luca; Lobov, Andrei; Lastra, José L. Martínez

doi:10.1080/0951192x.2017.1407874

Cited by 32 publications

(15 citation statements)

References 30 publications

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“…The migration towards knowledge-driven approaches would require rethinking of established industrial practices. The change would need the actions on all the architecture, starting from the controller devices in charge of industrial enjoinment to the higher level information systems, where the shift from databases to knowledge bases should be performed (Mohammed et al, 2018).…”

Section: Related Work Of Knowledge-based Methods For Management Of Mmentioning

confidence: 99%

The Design Approach of Knowledge-based Management System for Control of Manufacturing Processes of Woven Fabrics

Dzemydienė¹,

Arbataitis²,

Dzemyda³

2019

BJMC

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The aim of effective management of manufacturing processes requires special methods of knowledge management integrated in multi-layered architecture of components of enterprise recourse planning system. Our research work is devoted for extension of knowledge-based management system by integration of specific business management rules for adaptable control of manufacturing processes of woven fabrics. The proposed framework can help for manufacturing process realization of woven fabrics by solving key issues related to rules and data for product design and process planning. This could help knowledge-based system self-learn and change in order to cope with ever-changing business requirements. With this study, we are trying to fill the gap related with knowledge-based methods for effective manufacturing process of woven fabrics.

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Section: Related Work Of Knowledge-based Methods For Management Of Mmentioning

confidence: 99%

The Design Approach of Knowledge-based Management System for Control of Manufacturing Processes of Woven Fabrics

Dzemydienė¹,

Arbataitis²,

Dzemyda³

2019

BJMC

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“… The data can be utilized by researchers and developer of manufacturing systems that are specialized in optimizing manufacturing processes. The data can also be important for companies who develop Manufacturing Execution Systems (MES) and Enterprise Resources Planning (ERP) systems [4] . The FASTory Digital Twin data can be exploited in modelling discrete manufacturing processes or testing and validating optimization solutions for balancing the utilization of the manufacturing resources.…”

Section: Value Of the Datamentioning

confidence: 99%

Section: Value Of the Datamentioning

confidence: 99%

FASTory digital twin data

Mohammed

Lastra

2021

Data in Brief

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The vast adoption of machine learning techniques in developing smart solutions increases the need of training and testing data. This data can be either collected from physical systems or created using simulation tools. In this regard, this paper presents a set of data collected using a digital twin known as the FASTory Simulator. The data contains more than 100 K events which are collected during a simulated assembly process. The FASTory simulator is a replica of a real assembly line with web-based industrial controllers. The data have been collected using specific-developed orchestrator. During the simulated process, the orchestrator was able to record all the events that occurred in the system. The provided data contains raw JavaScript Object Notation (JSON) formatted data and filtered Comma Separated Values (CSV) formatted data. This data can be exploited in machine learning for modelling the behaviour of the production systems or as testing data for optimization solution for the production system. Finally, this data has been utilized in a research for comparing different data analysis approaches including Knowledge-based systems and data-based systems.

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“…Further, although it is not mandatory, RESTful web services frequently employ the concept of Create, Read, Update and Delete (CRUD) by using different HTTP request methods which are mapped to GET, POST, PUT and DELETE [24]. In regard of usage in industrial cases, RESTful web services have been included in many approaches as discussed in [25][26][27][28][29].…”

Section: Web Services and Hypermediamentioning

confidence: 99%

Implementing and Visualizing ISO 22400 Key Performance Indicators for Monitoring Discrete Manufacturing Systems

et al. 2018

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The employment of tools and techniques for monitoring and supervising the performance of industrial systems has become essential for enterprises that seek to be more competitive in today’s market. The main reason is the need for validating tasks that are executed by systems, such as industrial machines, which are involved in production processes. The early detection of malfunctions and/or improvable system values permits the anticipation to critical issues that may delay or even disallow productivity. Advances on Information and Communication Technologies (ICT)-based technologies allows the collection of data on system runtime. In fact, the data is not only collected but formatted and integrated in computer nodes. Then, the formatted data can be further processed and analyzed. This article focuses on the utilization of standard Key Performance Indicators (KPIs), which are a set of parameters that permit the evaluation of the performance of systems. More precisely, the presented research work demonstrates the implementation and visualization of a set of KPIs defined in the ISO 22400 standard-Automation systems and integration, for manufacturing operations management. The approach is validated within a discrete manufacturing web-based interface that is currently used for monitoring and controlling an assembly line at runtime. The selected ISO 22400 KPIs are described within an ontology, which the description is done according to the data models included in the KPI Markup Language (KPIML), which is an XML implementation developed by the Manufacturing Enterprise Solutions Association (MESA) international organization.

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Generic platform for manufacturing execution system functions in knowledge-driven manufacturing systems

Cited by 32 publications

References 30 publications

The Design Approach of Knowledge-based Management System for Control of Manufacturing Processes of Woven Fabrics

The Design Approach of Knowledge-based Management System for Control of Manufacturing Processes of Woven Fabrics

FASTory digital twin data

Implementing and Visualizing ISO 22400 Key Performance Indicators for Monitoring Discrete Manufacturing Systems

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