Bottleneck Detection Through Data Integration, Process Mining and Factory Physics-Based Analytics

Kumbhar, MaheshHögskolan i Skövde,Institutionen för ingenjörsvetenskap,Forskningsmiljön Virtuell produkt- och produktionsutveckling,Production and Automation Engineering (author)

CC BY-NC 4.0Corresponding Author: Mahesh Kumbhar, School of Engineering Science, University of Skövde, Skövde, Sweden; E-mail: mahesh.kumbhar@his.se
Production systems are evolving rapidly, thanks to key Industry 4.0 technologies such as production simulation, digital twins, internet-of-things, artificial intelligence, and big data analytics. The combination of these technologies can be used to meet the long-term enterprise goals of profitability, sustainability, and stability by increasing the throughput and reducing production costs. Owing to digitization, manufacturing companies can now explore operational level data to track the performance of systems making processes more transparent and efficient. This untapped granular data can be leveraged to better understand the system and identify constraining activities or resources that determine the system’s throughput. In this paper, we propose a data-driven methodology that exploits the technique of data integration, process mining, and analytics based on factory physics to identify constrained resources, also known as bottlenecks. To test the proposed methodology, a case study was performed on an industrial scenario were a discrete event simulation model is built and validated to run future what-if analyses and optimization scenarios. The proposed methodology is easy to implement and can be generalized to any other organization that captures event data.

TEKNIK OCH TEKNOLOGIER Maskinteknik Produktionsteknik, arbetsvetenskap och ergonomi hsv//swe
ENGINEERING AND TECHNOLOGY Mechanical Engineering Production Engineering, Human Work Science and Ergonomics hsv//eng
Process Mining
Factory Physics
Data Analytics
Manufacturing
Bottleneck Detection
Production and Automation Engineering
Produktion och automatiseringsteknik
VF-KDO
VF-KDO

Ng, Amos H. C.,1970-Högskolan i Skövde,Institutionen för ingenjörsvetenskap,Forskningsmiljön Virtuell produkt- och produktionsutveckling,Division of Industrial Engineering & Management, Uppsala University, Sweden,Production and Automation Engineering(Swepub:his)ngam (author)
Bandaru, Sunith,1984-Högskolan i Skövde,Institutionen för ingenjörsvetenskap,Forskningsmiljön Virtuell produkt- och produktionsutveckling,Production and Automation Engineering(Swepub:his)bans (author)
Högskolan i SkövdeInstitutionen för ingenjörsvetenskap (creator_code:org_t)

In:SPS2022Amsterdam; Berlin; Washington, DC : IOS Press, s. 737-74897816436826869781643682693

By the author/editor: Kumbhar, Mahesh; Ng, Amos H. C., ...; Bandaru, Sunith, ...

About the subject

ENGINEERING AND TECHNOLOGY: ENGINEERING AND ...; and Mechanical Engin ...; and Production Engin ...

Kungliga biblioteket hanterar dina personuppgifter i enlighet med EU:s dataskyddsförordning (2018), GDPR. Läs mer om hur det funkar här.
Så här hanterar KB dina uppgifter vid användning av denna tjänst.