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This paper provides a case study describing an approach to improving the efficiency of an information system (IS) by supporting processes outside the IS, using the ontology-driven knowledge management systems (KMS) as a mini-application in the area of so-called lean enterprise. Lean enterprise is focused on creating a maximal value for final customers while eliminating all kinds of waste and unnecessary costs, which significantly helps to increase the level of its competitiveness. It is about managerial decision-making, which can be in some cases contradictory (solving a local problem can cause a problem in another place). In this paper, we describe the KMS ATOM, which supports the innovation process in a lean enterprise. We show how the risk of wrong decisions due to contradictory effects can be eliminated by implementing a safety-critical system into the traditional IS. Our model is supported by Event-B modelling, a refinement-based formal modelling method, which is successfully used in important areas such as infrastructure, medicine, nuclear engineering and transportation (fire alarm systems, robotic surgery machines, braking systems in transportation, etc.). Nowadays, Event-B modelling is starting to be used for various management decision-making activities, and it is becoming a powerful competitiveness tool. This paper introduces a simple example of how Event-B modelling and its proof obligations can help improve and automate the decision-making process by eliminating potential threats of inefficient decisions.

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Digital twin technology has become one of the key directions of intelligent manufacturing with a strong relationship to product lifecycle management. It contributes to increasing efficiency and flexibility in solving highly complex problems in constantly changing conditions. However, many circumstances make the real implementation of effective scenarios generated by simulation software tools difficult. One of them are rigid working schedules that complicate flexible human resources planning in accordance with optimal production and logistics plans. This article aims to examine the role of the digital factory twin in advanced human resources planning. Using the case study method, a solution for better coordination of internal logistics processes and utilization of logistics staff based on discrete-event simulation is presented. Several scenarios were tested and results showed the inevitability of using flexible working schedules for maximum utilization of logistics staff. The purpose of this study is not only to show one special case of one company, but to emphasize the potential of these software tools to achieve long-term synergies in coordinating logistics, production and human resources management activities. As a result of this study, an extended physical-digitalphysical loop model is presented. This extension consists in adding the second loop including communication with HR portal.