Proceedings of ICLT 2022
Development of Intelligence Data-Driven Analysis Platform in Food Industry using Data Ingestion Tools
Natdanai Homkong; Adul Premprasert; Choncharoen Sawangrat; Thanawat Kaewwiroon
Department of Industrial Engineering, Faculty of Engineering, Chiang Mai University, Thailand; Thanakorn Vegetable Oil Products Co., Ltd., Samut Prakan, Thailand; Faculty of Engineering, Chiang Mai University, Thailand; Department of Industrial Engineering, Faculty of Engineering, Chiang Mai University, Thailand
International Conference on Logistics & Transport 2022, Krabi, Thailand, pp. 100-105
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Abstract
On one issue of the industry 4.0 criterion, the electronic information exchange depended on manufacturing control functions. In other departments, enterprise functions should be transformed into digital. In the case of the food industry, the step of manufacturing operations management (level 3) has necessary action to upgrade business planning and logistics (level 4) as follow as ISA 95 standards. The issues contain mix-up and fragmented data from all departments within organization because data of supply chain management, manufacturing and facilities cannot link that data together. There is affected to lack data analytics for the board immediately. Thus, the digital platform of datadriven and robotic process automation technology must be installed to bring data from all departments into one place by using a global cloud. The 5C architecture development for Industry 4.0 have been applied with the data ingestion concept to integrate information of all departments for initial investigation on exploratory data analysis. An analytics management was successfully to training machine learning for data-driven. While working standards that reduce the chance of human error, decrease unnecessary workload by using robots and allow employees to focus on other tasks that create value for the company. Robots will work in the whole production process 24 hours a day. The working standard in the office is paperless which reduces overall costs. Moreover, using real-time analytics allows engineers, managers, and c-levels to immediately know what is happening in the factory without having to hold weekly meetings of all departments.
Keywords
Artificial intelligence Data-driven; Digitalization; Data ingestion; Robotic process automation
Citation
Natdanai Homkong; Adul Premprasert; Choncharoen Sawangrat; Thanawat Kaewwiroon (2022). Development of Intelligence Data-Driven Analysis Platform in Food Industry using Data Ingestion Tools. Proceedings of the International Conference on Logistics & Transport (ICLT 2022), Krabi, Thailand, pp. 100-105.