TY - GEN
T1 - Enhancing the steel tube manufacturing process with a zero defects approach
AU - Sousa, João
AU - Ferreira, José
AU - Lopes, Carlos
AU - Sarraipa, João
AU - Silva, João
N1 - Funding Information:
info:eu-repo/grantAgreement/EC/H2020/825631/EU#
PY - 2021/2/16
Y1 - 2021/2/16
N2 - The continuous thrive for working safety, customer satisfaction and increasing profits for companies has led to numerous manufacturing and management strategies. One of the most promising strategies nowadays is Zero Defects that focuses on the elimination of defected parts in the manufacturing processes. The benefits of Zero Defect implementation in the manufacturing industry are mainly related to the reduction of scrap material, and everything that does not bring any added value to the product. The result is a reduction of the company's expenditure for dealing with defective products. In spite the concept not being new, the practical application of such strategies were limited by technological constraints and high investment costs. With the Industry 4.0 evolution, some Zero Defects concepts are more accessible due to the availability of sensors and data related techniques such as Machine Learning and Big Data although a lot of work is still required for component integration to enhance the capability of the heterogeneous technologies. The quality of the steel tubes is evaluated by sampling and relies on the expertise of the operators for checking for nonconformities. When a defect is detected, the process parameters are adjusted based on prior experience. However, since this is a continuous process, the delay between the appearance of a defect in the process and its awareness leads to a considerable amount of produced scrap material. Worst-case scenario, the defective product can be delivered to the customer damaging the customers trust and leading to additional replacement costs. This paper addresses the application of the Zero Defects approach to the steel tube manufacturing industry. This approach is part of the Zero Defects Manufacturing Platform EU project that is based around a Service Oriented Architecture and microservices approach capable of building, running and managing specific use-case oriented software applications called zApps. The Zero Defects methodology to design a zApp based on key criteria for the steel tube industry is described. Additionally, the envisioned zApps to monitor all the produced steel tube during the manufacturing process are detailed. The inspection systems uses a scanning camera and a laser profile scanner to capture the steel tube defects during manufacturing and prior to packaging. Although the ultimate goal is to eliminate the cause of the defective products, the objective of the zApp is to increase the number of detections of defective products based on industry standards and reduce the amount of generated scrap material.
AB - The continuous thrive for working safety, customer satisfaction and increasing profits for companies has led to numerous manufacturing and management strategies. One of the most promising strategies nowadays is Zero Defects that focuses on the elimination of defected parts in the manufacturing processes. The benefits of Zero Defect implementation in the manufacturing industry are mainly related to the reduction of scrap material, and everything that does not bring any added value to the product. The result is a reduction of the company's expenditure for dealing with defective products. In spite the concept not being new, the practical application of such strategies were limited by technological constraints and high investment costs. With the Industry 4.0 evolution, some Zero Defects concepts are more accessible due to the availability of sensors and data related techniques such as Machine Learning and Big Data although a lot of work is still required for component integration to enhance the capability of the heterogeneous technologies. The quality of the steel tubes is evaluated by sampling and relies on the expertise of the operators for checking for nonconformities. When a defect is detected, the process parameters are adjusted based on prior experience. However, since this is a continuous process, the delay between the appearance of a defect in the process and its awareness leads to a considerable amount of produced scrap material. Worst-case scenario, the defective product can be delivered to the customer damaging the customers trust and leading to additional replacement costs. This paper addresses the application of the Zero Defects approach to the steel tube manufacturing industry. This approach is part of the Zero Defects Manufacturing Platform EU project that is based around a Service Oriented Architecture and microservices approach capable of building, running and managing specific use-case oriented software applications called zApps. The Zero Defects methodology to design a zApp based on key criteria for the steel tube industry is described. Additionally, the envisioned zApps to monitor all the produced steel tube during the manufacturing process are detailed. The inspection systems uses a scanning camera and a laser profile scanner to capture the steel tube defects during manufacturing and prior to packaging. Although the ultimate goal is to eliminate the cause of the defective products, the objective of the zApp is to increase the number of detections of defective products based on industry standards and reduce the amount of generated scrap material.
KW - Data acquisition
KW - Digital manufacturing platform
KW - Image processing
KW - Industrial internet of things
KW - Zero defects
UR - http://www.scopus.com/inward/record.url?scp=85101217281&partnerID=8YFLogxK
U2 - 10.1115/IMECE2020-24678
DO - 10.1115/IMECE2020-24678
M3 - Conference contribution
AN - SCOPUS:85101217281
T3 - ASME International Mechanical Engineering Congress and Exposition, Proceedings (IMECE)
BT - Advanced Manufacturing
PB - ASME - The American Society of Mechanical Engineers
T2 - ASME 2020 International Mechanical Engineering Congress and Exposition, IMECE 2020
Y2 - 16 November 2020 through 19 November 2020
ER -