TY - GEN
T1 - A Flexible and Intelligent Production System for Process Planning and Enterprise Performance Optimization
AU - Fernandes, Ederson Carvalhar
AU - Iaksch, Jaqueline Sebastiany
AU - Ferreira Tabor, Sandro Jessé
AU - Romanel, Luiz Gustavo
AU - Brown, Liam
AU - Borsato, Milton
N1 - Publisher Copyright:
© 2023 The Authors.
PY - 2023/11/7
Y1 - 2023/11/7
N2 - Many companies have been expending considerable efforts to continuously improve manufacturing processes to ensure their competitiveness and remain in the market. Value Stream Mapping is a strategic tool that makes it possible to visualize the macro of production to assist in planning and decision-making. It is a process mapping that considers the workflow of a product from the arrival of the raw material to the result that is delivered to the customer. Despite the benefits this tool has provided to organizations, the time for its development is still very high, as its data is still filled manually, allowing its analysis to be error-prone. Digital technologies have brought several improvements to the methods and tools of organizations. With the goal of obtaining contributions to engineering through transdisciplinary approaches to decision support tools and methods, therefore, this study will present the development of a dynamic web application using data analytics and machine learning to visualize, identify bottlenecks, predict, and update data in current and future state mappings. Intelligent systems tend to eliminate the routine activities of engineering, so this application will allow engineers and technicians to dedicate more time to dedicate themselves exclusively to activities that require a more challenging level of managerial decision-making.
AB - Many companies have been expending considerable efforts to continuously improve manufacturing processes to ensure their competitiveness and remain in the market. Value Stream Mapping is a strategic tool that makes it possible to visualize the macro of production to assist in planning and decision-making. It is a process mapping that considers the workflow of a product from the arrival of the raw material to the result that is delivered to the customer. Despite the benefits this tool has provided to organizations, the time for its development is still very high, as its data is still filled manually, allowing its analysis to be error-prone. Digital technologies have brought several improvements to the methods and tools of organizations. With the goal of obtaining contributions to engineering through transdisciplinary approaches to decision support tools and methods, therefore, this study will present the development of a dynamic web application using data analytics and machine learning to visualize, identify bottlenecks, predict, and update data in current and future state mappings. Intelligent systems tend to eliminate the routine activities of engineering, so this application will allow engineers and technicians to dedicate more time to dedicate themselves exclusively to activities that require a more challenging level of managerial decision-making.
KW - AI
KW - Data Analytics
KW - Machine Learning
KW - Production
KW - Value Stream Mapping
UR - http://www.scopus.com/inward/record.url?scp=85184296031&partnerID=8YFLogxK
U2 - 10.3233/ATDE230642
DO - 10.3233/ATDE230642
M3 - Conference contribution
AN - SCOPUS:85184296031
T3 - Advances in Transdisciplinary Engineering
SP - 482
EP - 491
BT - Leveraging Transdisciplinary Engineering in a Changing and Connected World - Proceedings of the 30th ISTE International Conference on Transdisciplinary Engineering
A2 - Cooper, Adam
A2 - Koomsap, Pisut
A2 - Stjepandic, Josip
PB - IOS Press BV
T2 - 30th ISTE International Conference on Transdisciplinary Engineering: Leveraging Transdisciplinary Engineering in a Changing and Connected World, TE 2023
Y2 - 11 July 2023 through 14 July 2023
ER -