User-Friendly MES Interfaces:Recommendations for an AI-Based Chatbot Assistance in Industry 4.0 Shop Floors

The purpose of this paper is to study an Industry 4.0 scenario of ‘technical assistance’ and use manufacturing execution systems (MES) to address the need for easy information extraction on the shop floor. We identify specific requirements for a user-friendly MES interface to develop (and test) an approach for technical assistance and introduce a chatbot with a prediction system as an interface layer for MES. The chatbot is aimed at production coordination by assisting the shop floor workforce and learn from their inputs, thus acting as an intelligent assistant. We programmed a prototype chatbot as a proof of concept, where the new interface layer provided live updates related to production in natural language and added predictive power to MES. The results indicate that the chatbot interface for MES is beneficial to the shop floor workforce and provides easy information extraction, compared to the traditional search techniques. The paper contributes to the manufacturing information systems field and demonstrates a human-AI collaboration system in a factory. In particular, this paper recommends the manner in which MES based technical assistance systems can be developed for the purpose of easy information retrieval

№ 1. Прохання парафіяльної Ради Ново-Слов’янського кафедрального собору до отця О. Ярещенка про відправлення архієрейської служби на «Зелені Свята» від 18 травня 1923 р.

Публікація Д. Бойко, І. Бухарєвої, С. Кокіна, П. Кулаковського

Development of a Collaborative Platform for Closed Loop Production Control

Part 8: Collaboration Platform IssuesInternational audienceIn today’s turbulent market, the way data are used in production is one of the key aspects to maintain or increase a manufacturing company’s ability to compete. Even though most companies are aware of the advantages of collecting, analyzing and using data, the majority of them do not exploit these fully. Thus, IT systems and sensors are integrated into the shop floor in order to deal with the current challenges, leading to an overwhelming amount of data without contributing to an improvement of production control. Because of developments like digitization and Industry 4.0, there is an innumerable amount of existing research focusing on data analytics, artificial intelligence and pattern recognition. However, research on collaborative platforms in traditional production control still needs improvement. Therefore, the main goal of this paper is to present a platform based closed loop production control and to discuss the relevant data. The collaborative platform represents the basis for a future analysis of high-resolution data using cognitive systems in order for companies to maximize the automation of their production. A use case at the end of the paper shows the potential implementation of the findings in practice