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Mass individualized production refers to the mass production of individualized products. It becomes important for delivering a personalized customer experience in the Industrial Revolution 4.0 era. Developing seamless value chain integration between enterprises to achieve mass individualized production is challenging. Based on Reference Architecture Model Industrie 4.0 (RAMI 4.0), this paper aims to address two major challenges, which are asset modeling and integration, and data communication and brokering in a value chain data exchange ecosystem. This paper proposes a communication architecture that enables both vertical and horizontal value-chain integration. A proof-of-concept is built, which involves two stakeholders. The first is the individualized juice online ordering system, named PEC, and the second is a highly automated individualized mixed juice production manufacturing line, named OMIS. Three different tests are conducted in the experiments. The first is to test the creation of assets wrapped in the asset administration shell. The second is to test the connectivity between the Asset Brokering Manager (ABM) Connector and the ABM Portal. Last is to test the connectivity performance between two Asset Administration Systems. As a result, the experiments successfully created the asset instance data accurately, and the data were published in the ABM Portal for subscription by PEC and OMIS. The connectivity tests from OMIS to PEC, and vice versa, were successful, with the time taken of 114 and 121 ms, respectively.

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Malaysia agriculture sector has been heavily impacted by the pandemic and thus disrupted the agricultural food supply chain since early 2020. The problems of lack of labor, less production, movement restriction, market close, all has led to dramatically drop of income or even zero-income specially impacted the smallholders. Agriculture supply chain needed to be strengthened through a tighten collaboration between the sector’s supply chain stakeholders. Technology always the solutions for most of the problems, data can be collected through technology solutions such as Internet of Things, market insight can be achieved by artificial intelligent analysis and prediction, and such. The paper focuses on introducing the supply chain connectivity through an information sharing platform, Agrolink. It is an aggregator of the information resources that link all the elements of the agricultural food supply chain in Malaysia, which accessible by farmers, producers, service providers of the supply chain (including processing, logistics, finance, retail, etc.), agriculture food associations, government agencies, and educational research institutions. The paper discusses the methodologies adopted to build the information toolbox. Keywords: Information toolbox, Food supply chain, Agricultural ecosystem

Overall Equipment Effectiveness (OEE) has been used by manufacturers as a key metric to identify how productive a production operation is, during the planned production time. While Industrial Internet of Things (IIoT) can be leveraged with data science, predictive maintenance becomes a better option for manufacturers to maintain their equipment. In this study, a simulation of predictive maintenance was done by using Classification and Regression Tree (CART) algorithm to predict machine failure. We also discussed the possible improvement of predictive maintenance to OEE. Keywords: Overall Equipment Effectiveness, Industry 4.0, Predictive Maintenance