An approach for implementing key performance indicators of a discrete manufacturing simulator based on the ISO 22400 standard

Muhammad, Usman; Ferrer, Borja Ramis; Mohammed, Wael M.; Lastra, José L. Martínez

doi:10.1109/icphys.2018.8390779

Cited by 7 publications

(7 citation statements)

References 16 publications

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“…ISO 22400 and ANSI ISA-95 work together to define the KPIs in three sorts of MOM industries; batch, Continuous, and Discrete [ 88 , 89 ]. ISO 22400 sets the requirements for a KPI, and MESA International has produced KPI-ML, an XML version of the ISO 22400 Specification currently being used to record, interact, and exchange KPI knowledge [ 90 ]. ISO 22400 is a multinational, non-profit organization of production firms, IT manufacturers, systems integration, vendor consultancy, researchers, authors, academics, and students.…”

Section: Methodologiesmentioning

confidence: 99%

“…The data collected from engine sensors are for glance viewing [ 2 , 70 ]. Before any system failures, these platforms provide predictive maintenance information to airline maintenance teams and passengers with new value-added information, and they allow for a new quality management approach by predictive maintenance [ 90 ]. Rolls-Royce can use comprehensive data analysis, intelligent sensors, AI, and platform construction to retain quality control by predictive maintenance.…”

Section: Methodologiesmentioning

confidence: 99%

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Performance Measurement System and Quality Management in Data-Driven Industry 4.0: A Review

Tambare¹,

Meshram²,

Lee

et al. 2021

Sensors

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The birth of mass production started in the early 1900s. The manufacturing industries were transformed from mechanization to digitalization with the help of Information and Communication Technology (ICT). Now, the advancement of ICT and the Internet of Things has enabled smart manufacturing or Industry 4.0. Industry 4.0 refers to the various technologies that are transforming the way we work in manufacturing industries such as Internet of Things, cloud, big data, AI, robotics, blockchain, autonomous vehicles, enterprise software, etc. Additionally, the Industry 4.0 concept refers to new production patterns involving new technologies, manufacturing factors, and workforce organization. It changes the production process and creates a highly efficient production system that reduces production costs and improves product quality. The concept of Industry 4.0 is relatively new; there is high uncertainty, lack of knowledge and limited publication about the performance measurement and quality management with respect to Industry 4.0. Conversely, manufacturing companies are still struggling to understand the variety of Industry 4.0 technologies. Industrial standards are used to measure performance and manage the quality of the product and services. In order to fill this gap, our study focuses on how the manufacturing industries use different industrial standards to measure performance and manage the quality of the product and services. This paper reviews the current methods, industrial standards, key performance indicators (KPIs) used for performance measurement systems in data-driven Industry 4.0, and the case studies to understand how smart manufacturing companies are taking advantage of Industry 4.0. Furthermore, this article discusses the digitalization of quality called Quality 4.0, research challenges and opportunities in data-driven Industry 4.0 are discussed.

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Section: Methodologiesmentioning

confidence: 99%

Section: Methodologiesmentioning

confidence: 99%

Performance Measurement System and Quality Management in Data-Driven Industry 4.0: A Review

Tambare¹,

Meshram²,

Lee

et al. 2021

Sensors

View full text Add to dashboard Cite

show abstract

“…Previously, an approach for implementing key performance indicators based on the ISO 22400 standard was presented in [15]. However, the authors left as further work the implementation of KPI visualization.…”

Section: Discussionmentioning

confidence: 99%

“…The five components are: The Knowledge based System Service, the Manufacturing Plant, the Orchestration Engine, the KPI Implementation and the User Interface, which is the component that provides the users with the visualization of selected KPIs. The implementation of the latter component was the task left as further work in [15], i.e., the principal contribution of this article. Besides the implementation of each component, the results shown in Section 5 illustrate the different graphs that are included in the user interface, which provides the visualization of KPIs.…”

Section: Main Components Of the Approachmentioning

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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“…Borsos et al [38], explored the relationship between the KPIs and the objectives set by the manufacturing industries in order to determine the waste in the production process. Muhammed et al [39], cited few manufacturing KPIs and implemented them on multi robot line simulator to improve its performance from the results obtained by the KPIs. Iuga et al [40], listed few shop floor KPIs for automotive industries based on the interviews conducted with various automotive manufacturers.…”

Section: Literature Reviewmentioning

confidence: 99%

Literature Survey about Elements of Manufacturing Shop Floor Operation Key Performance Indicators

Khan

Ahmad

2019

2019 5th International Conference on Control, Automation and Robotics (ICCAR)

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In the era of globalisation, manufacturing industries are compelled to continuously monitor their manufacturing operations to maintain competitiveness. As a result, manufacturers have integrated several measurement models to inspect their manufacturing operations. These models comprise of a set of Key Performance Indicators (KPIs), which are capable to enumerate the effectiveness, competence, efficiency and proficiency of manufacturing operations. This paper presents a review of manufacturing shop floor operation KPIs that has been studied in the recent literature. Based on the reviewed literature author proposes various KPI elements such as: description, category, scope, formula, unit of measure, range, trend, mode of display, viewers and manufacturing approach. These elements can help manufacturers to better describe, classify, analyse and measure the appropriate KPIs for their shop floor operations. Thus, enabling manufacturers to accomplish and uphold great quality, increased productivity and throughput.

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An approach for implementing key performance indicators of a discrete manufacturing simulator based on the ISO 22400 standard

Cited by 7 publications

References 16 publications

Performance Measurement System and Quality Management in Data-Driven Industry 4.0: A Review

Performance Measurement System and Quality Management in Data-Driven Industry 4.0: A Review

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

Literature Survey about Elements of Manufacturing Shop Floor Operation Key Performance Indicators

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