Industrial site selection is a strategic decision that involves several criteria with consideration for technical, economic, social, environmental, and political issues. These criteria are generally described using a number of different indicators, expressed in quantitative and qualitative ways with some possible uncertainty. Decision making requires, therefore, appropriate tools to enable data collection, storage, analysis, fusion, and knowledge management to address this complex, multifaceted scenario. This paper presents a Comprehensive Method for Industrial Site Selection (CMISS), an innovative approach for reasoning uncertainty and efficiently finding the most suitable solution based on a set of interacting decision support systems. Experimental results show that the proposed approach provides accurate results in the region of interest, coinciding with the choices of expert analysts.
Production systems that are by their structure designed according to principies of group technology must, despite their perfection, rapidl adapt to changes in surroundings and engage in a battle with their market rivais. First of all, they must get doser to customers and suppiier representing one of first principies of iean phiiosophy. it is one of the ways to successfuily vaiorise comparative values with competitio despite its internal restructuring. This paper presents the infiuence of certain lean tools as well as application of statisticai anaiyses, simulation and graphics tools for achieving greater effectiveness and efficiency of production systems. Appiication or integration of thes tools enables shortening of the production cyde, reduces the degree of complexity of materiai flows, reduces the suppiies and expenditur of energy resources whiie it creates an increased degree of functionaiity of the organisation, utilization of workspace etc. Combination different toois presented in this paper can valorise new technologicai, organisationai and informationai achievements in production that w secure an even better position on the market for industrial systems.
It became more than evident that the era of Industry 4.0 is upon us, where industrial manufacturing companies are facing strong demand to increase their productivity by realizing smart factories and smart manufacturing. With the advantages of high-tech devices and solutions such as IPCs, industrial automation and machine automation technologies, hardware-software integration and various others, it is now possible to foster the development of Industry 4.0 through three logical steps. The first step considers the implementation of equipment connectivity: devices, machines, production lines and factories are connected to the system, and therefore, data transparency as well as information visualization can be obtained. In addition, the second step involves data collection and integration, as well as valued-added products and services that are introduced for smart manufacturing services. Lastly, the third step of intelligent innovative services is the enabling of intelligent machinery and big data analysis. Given the aforementioned, smart factory can be defined as a factory which harmonically implements Machine Automation, Equipment Monitoring & Optimization, Machine Monitoring & Predictive Maintenance, MES Integration & Production Traceability, Factory Energy Management System and Factory Environment Monitoringdeveloped with integrated automation and cloud innovation for industry 4.0. Having in mind that the aim of this paper is to review the possibilities and concerns of Energy Management in Industry 4.0 Ecosystem, this topic will be devoted to the greatest attention, while the importance of other equally relevant topics that are simply not the subject of this review should not be diminished or underestimated.
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