Reducing the Configuration Burden in Automation Systems - Case Study in a Modern Brewery

Abstract

Enterprises operating industrial control and automation systems, in a bid to increase profitability, are demanding ‘smarter’ shop floor operations, and are becoming ever more ‘data-driven’ in their decision making. IIoT and Industry 4.0 come with the promise of unlocking vast amounts of previously unavailable data from shop-floor devices and systems. In meeting this thirst for data, there is a significant engineering burden to correctly configure and connect devices and software systems.This paper presents two general approaches that allow connections between data sources and sinks in automation systems to be rapidly configured en masse. These techniques, scripting and model-based, can automate the manual, repetitive, and error-prone data point configuration task. A case study applying implementations of these techniques in a modern brewery’s process control and automation systems is presented. It demonstrates the significant level of reduction in configuration burden that has been achieved, especially in the case of the model-based approach.By utilitising these techniques, the cost, time, and error-rate involved in the configuration of industrial control and automation software systems can be greatly reduced. These improvements in engineering efficiency can lead to previously infeasible projects becoming achievable, and the extension of the lifetimes and capabilities of existing plants and equipment.