Autonomous Cycles of Data Analysis Tasks for the Automation of the Production Chain of MSMEs for the Agroindustrial Sector

Abstract

In this paper, we propose autonomous cycles of data analysis tasks for the automation of the production chains aimed to improve the productivity of Micro, Small and Medium Enterprises (MSMEs) in the context of agroindustry. In the autonomous cycles of data analysis tasks, each task interacts with the others and has different functions, in order to reach the goal of the cycle. In this article, we identify three industrial-automation processes within the production chain, in which autonomous cycles can be applied. The first cycle is responsible to identify the type of input to be transformed—such as quantity, quality, time, and cost—based on information from the organization and its context. The second cycle selects the technological level used in the raw-material transformation, characterizing the platform of plant processing. The last cycle identifies the level of specialization of the generated product, such as the quality and value of the product. Finally, we apply the first autonomous cycle to define the type of input to be transformed in a coffee factory.

Keywords

• production-chain
• agroindustry
• autonomous computing
• artificial intelligence
• data analysis
• machine learning