The Relationship between Fuzzy Reasoning and Its Temporal Characteristics for Knowledge Management

The knowledge management systems based on artificial reasoning (KMAR) tries to provide computers the capabilities of performing various intelligent tasks for which their human users resort to their knowledge and collective intelligence. There is a need for incorporating aspects of time and imprecision into knowledge management systems, considering appropriate semantic foundations. The aim of this paper is to present the FRTES, a real-time fuzzy expert system, embedded in a knowledge management system. Our expert system is a special possibilistic expert system, developed in order to focus on fuzzy knowledge.Knowledge Management, Artificial Reasoning, predictability

Knowledge Management in the Fourth Industrial Revolution: Mapping the Literature and Scoping Future Avenues

Due to increased competitive pressure, modern organizations tend to rely on knowledge and its exploitation to sustain a long-term advantage. This calls for a precise understanding of knowledge management (KM) processes and, specifically, how knowledge is created, shared/transferred, acquired, stored/retrieved, and applied throughout an organizational system. However, since the beginning of the new millennium, such KM processes have been deeply affected and molded by the advent of the fourth industrial revolution, also called Industry 4.0, which involves the interconnectedness of machines and their ability to learn and share data autonomously. For this reason, the present study investigates the intellectual structure and trends of KM in Industry 4.0. Bibliometric analysis and a systematic literature review are conducted on a total of 90 relevant articles. The results reveal 6 clusters of keywords, subsequently explored via a systematic literature review to identify potential stream of this emergent field and future research avenues capable of producing meaningful advances in managerial knowledge of Industry 4.0 and its consequences

Business process trends

Business process and business process management (BPM) concepts have matured over the years and new technology, concepts, standards and solutions appear. In this chapter we will therefore focus on the current and future process trends. We will elaborate on the importance of trends, the maturity of the subject, giving a perspective on what emerging trends, industry trends, mega trends are, what is hyped at the moment, and what has reached a market adoption where it has started to become the de facto standard in terms of mega trends that has achieved a dominant position by public acceptance

Graph-based reasoning in collaborative knowledge management for industrial maintenance

Capitalization and sharing of lessons learned play an essential role in managing the activities of industrial systems. This is particularly the case for the maintenance management, especially for distributed systems often associated with collaborative decision-making systems. Our contribution focuses on the formalization of the expert knowledge required for maintenance actors that will easily engage support tools to accomplish their missions in collaborative frameworks. To do this, we use the conceptual graphs formalism with their reasoning operations for the comparison and integration of several conceptual graph rules corresponding to different viewpoint of experts. The proposed approach is applied to a case study focusing on the maintenance management of a rotary machinery system

Phronetic leadership style evaluation with a fuzzy logic application

The purpose of leadership style assessments is to determine the basic features and characteristics of leadership behaviours and to reveal the leader’s personality traits and abilities and to increase their self-awareness. The style can be, for example, democratic, autocratic, bureaucratic, laissez-faire, strategic, visionary, transformational, or transactional. However, ordinary assessments do not help leaders analyze their knowledge and wisdom behind their behaviours. The Wisdom Cube seeks to explain wisdom through the four dimensions of wisdom and provides a practical way of understanding the knowledge and wisdom in leadership. By utilising the dimensions and planes of the Wisdom Cube, we can find the way from data handling, information processing, and knowledge creation to wisdom generation. The aim of this research is, therefore, to reveal the ontology of the phronetic leader and to create a practical evaluation tool for leaders. The content of the article covers the elements of the Wisdom Cube, presents related efforts to measure and analyze phronetic leadership characteristics, and shows the practical results of the first test runs with the fuzzy logic-based application. The personal deep understanding of the leadership traits may then help the leaders to turn their current leadership styles more phronetic