Intelligent systems in manufacturing: current developments and future prospects

Global competition and rapidly changing customer requirements are demanding increasing changes in manufacturing environments. Enterprises are required to constantly redesign their products and continuously reconfigure their manufacturing systems. Traditional approaches to manufacturing systems do not fully satisfy this new situation. Many authors have proposed that artificial intelligence will bring the flexibility and efficiency needed by manufacturing systems. This paper is a review of artificial intelligence techniques used in manufacturing systems. The paper first defines the components of a simplified intelligent manufacturing systems (IMS), the different Artificial Intelligence (AI) techniques to be considered and then shows how these AI techniques are used for the components of IMS

Group Decision-Making Based on Artificial Intelligence: A Bibliometric Analysis

Decisions concerning crucial and complicated problems are seldom made by a single person. Instead, they require the cooperation of a group of experts in which each participant has their own individual opinions, motivations, background, and interests regarding the existing alternatives. In the last 30 years, much research has been undertaken to provide automated assistance to reach a consensual solution supported by most of the group members. Artificial intelligence techniques are commonly applied to tackle critical group decision-making difficulties. For instance, experts' preferences are often vague and imprecise; hence, their opinions are combined using fuzzy linguistic approaches. This paper reports a bibliometric analysis of the ample literature published in this regard. In particular, our analysis: (i) shows the impact and upswing publication trend on this topic; (ii) identifies the most productive authors, institutions, and countries; (iii) discusses authors' and journals' productivity patterns; and (iv) recognizes the most relevant research topics and how the interest on them has evolved over the years

Fuzzy segmentation of postmodern tourists.

In postmodern tourism, the experiences of each tourist could not be summarized only through a unique perspective but multiple and disjointed perspectives are necessary. The aim of this paper is to create a nexus between postmodern tourist and fuzzy clustering, and to propose a suitable clustering procedure to segment postmodern tourists. From a methodological perspective, the main contribution of this paper is related to the use of the fuzzy theory from the beginning to the end of the clustering process. Furthermore, the suggested procedure is capable of analysing the uncertainty and vagueness that characterise the experiences and perceptions of postmodern consumers. From a managerial perspective, fuzzy clustering methods offer to practitioners a more realistic multidimensional description of the market not forcing consumers to belong to one cluster. Moreover, the results are easy and comprehensible to read since they are similar to those obtained with more traditional clustering techniques