Manufacturing industry profoundly impact economic and societal progress. As being a commonly accepted term for research centers and universities, the Industry 4.0 initiative has received a splendid attention of the business and research community. Although the idea is not new and was on the agenda of academic research in many years with different perceptions, the term “Industry 4.0” is just launched and well accepted to some extend not only in academic life but also in the industrial society as well. While academic research focuses on understanding and defining the concept and trying to develop related systems, business models and respective methodologies, industry, on the other hand, focuses its attention on the change of industrial machine suits and intelligent products as well as potential customers on this progress. It is therefore important for the companies to primarily understand the features and content of the Industry 4.0 for potential transformation from machine dominant manufacturing to digital manufacturing. In order to achieve a successful transformation, they should clearly review their positions and respective potentials against basic requirements set forward for Industry 4.0 standard. This will allow them to generate a well-defined road map. There has been several approaches and discussions going on along this line, a several road maps are already proposed. Some of those are reviewed in this paper. However, the literature clearly indicates the lack of respective assessment methodologies. Since the implementation and applications of related theorems and definitions outlined for the 4th industrial revolution is not mature enough for most of the reel life implementations, a systematic approach for making respective assessments and evaluations seems to be urgently required for those who are intending to speed this transformation up. It is now main responsibility of the research community to developed technological infrastructure with physical systems, management models, business models as well as some well-defined Industry 4.0 scenarios in order to make the life for the practitioners easy. It is estimated by the experts that the Industry 4.0 and related progress along this line will have an enormous effect on social life. As outlined in the introduction, some social transformation is also expected. It is assumed that the robots will be more dominant in manufacturing, implanted technologies, cooperating and coordinating machines, self-decision-making systems, autonom problem solvers, learning machines, 3D printing etc. will dominate the production process. Wearable internet, big data analysis, sensor based life, smart city implementations or similar applications will be the main concern of the community. This social transformation will naturally trigger the manufacturing society to improve their manufacturing suits to cope with the customer requirements and sustain competitive advantage. A summary of the potential progress along this line is reviewed in introduction of the paper. It is so obvious that the future manufacturing systems will have a different vision composed of products, intelligence, communications and information network. This will bring about new business models to be dominant in industrial life. Another important issue to take into account is that the time span of this so-called revolution will be so short triggering a continues transformation process to yield some new industrial areas to emerge. This clearly puts a big pressure on manufacturers to learn, understand, design and implement the transformation process. Since the main motivation for finding the best way to follow this transformation, a comprehensive literature review will generate a remarkable support. This paper presents such a review for highlighting the progress and aims to help improve the awareness on the best experiences. It is intended to provide a clear idea for those wishing to generate a road map for digitizing the respective manufacturing suits. By presenting this review it is also intended to provide a hands-on library of Industry 4.0 to both academics as well as industrial practitioners. The top 100 headings, abstracts and key words (i.e. a total of 619 publications of any kind) for each search term were independently analyzed in order to ensure the reliability of the review process. Note that, this exhaustive literature review provides a concrete definition of Industry 4.0 and defines its six design principles such as interoperability, virtualization, local, real-time talent, service orientation and modularity. It seems that these principles have taken the attention of the scientists to carry out more variety of research on the subject and to develop implementable and appropriate scenarios. A comprehensive taxonomy of Industry 4.0 can also be developed through analyzing the results of this review.

Literature review of Industry 4.0 and related technologies

Buildings are among the largest consumers of electricity in the US. A significant portion of this energy use in buildings can be attributed to HVAC systems used to maintain comfort for occupants. In most cases these building HVAC systems run on fixed schedules and do not employ any fine grained control based on detailed occupancy information. In this paper we present the design and implementation of a presence sensor platform that can be used for accurate occupancy detection at the level of individual offices. Our presence sensor is low-cost, wireless, and incrementally deployable within existing buildings. Using a pilot deployment of our system across ten offices over a two week period we identify significant opportunities for energy savings due to periods of vacancy. Our energy measurements show that our presence node has an estimated battery lifetime of over five years, while detecting occupancy accurately. Furthermore, using a building simulation framework and the occupancy information from our testbed, we show potential energy savings from 10% to 15% using our system.

[ACM Press the 2nd ACM Workshop - Zurich, Switzerland (2010.11.02-2010.11.02)] Proceedings of the 2nd ACM Workshop on Embedded Sensing Systems for Energy-Efficiency in Building - BuildSys \'10 - Occupancy-driven energy management for smart building automation

Preface. Automatic Train Operation System by Predictive Fuzzy Control (S. Yasunobu, S. Miyamoto). Application of Fuzzy Reasoning to the Water Purification Process (O. Yagashita, O. Itoh, M. Sugeno). The Application of a Fuzzy Controller to the Control of a Multi-Degree-of-Freedom Robot Arm (E.M. Scharf, N.J. Mandic). Optimizing Control of a Diesel Engine (Y. Murayama et al.). Development of Performance Adaptive Fuzzy Controllers with Application to Continuous Casting Plants (G. Bartolini et al.). A Fuzzy Logic Controller for Aircraft Flight Control (L.I. Larkin). Automobile Speed Control System Using a Fuzzy Logic Controller (S. Murakami, M. Maeda). An Experimental Study on Fuzzy Parking Control Using a Model Car (M. Sugeno, K. Murakami). A Fuzzy Controller in Turning Process Automation (Y. Sakai, K. Ohkusa). Design of Fuzzy Control Algorithms with the Aid of Fuzzy Models (W. Pedrycz). Human Operator's Fuzzy Model in Man-Machine System with a Nonlinear Controlled Object (K. Matsushima, H. Sugiyama). The Influence of Some Parameters on the Accuracy of a Fuzzy Model (J.B. Kiszka, M.E. Kochanska, D.S. Sliwinska). A Microprocessor Based Fuzzy Controller for Industrial Purposes (T. Yamazaki, M. Sugeno). The Application of Fuzzy and Artificial Intelligence Methods in the Building of a Blast Furnace Smelting Process Model (H. Zhao, M. Ma). An Annotated Bibliography of Fuzzy Control (R.M. Tong).

Industrial applications of fuzzy control

Decision making trial and evaluation laboratory (DEMATEL) is considered as an effective method for the identification of cause-effect chain components of a complex system. It deals with evaluating interdependent relationships among factors and finding the critical ones through a visual structural model. Over the recent decade, a large number of studies have been done on the application of DEMATEL and many different variants have been put forward in the literature. The objective of this study is to review systematically the methodologies and applications of the DEMATEL technique. We reviewed a total of 346 papers published from 2006 to 2016 in the international journals. According to the approaches used, these publications are grouped into five categories: classical DEMATEL, fuzzy DEMATEL, grey DEMATEL, analytical network process- (ANP-) DEMATEL, and other DEMATEL. All papers with respect to each category are summarized and analyzed, pointing out their implementing procedures, real applications, and crucial findings. This systematic and comprehensive review holds valuable insights for researchers and practitioners into using the DEMATEL in terms of indicating current research trends and potential directions for further research.

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DEMATEL Technique: A Systematic Review of the State-of-the-Art Literature on Methodologies and Applications

This paper surveys neuro fuzzy systems (NFS) development using classification and literature review of articles for the last decade (2002-2012) to explore how various NFS methodologies have been developed during this period. Based on the selected journals of different NFS applications and different online database of NFS, this article surveys and classifies NFS applications into ten different categories such as student modeling system, medical system, economic system, electrical and electronics system, traffic control, image processing and feature extraction, manufacturing and system modeling, forecasting and predictions, NFS enhancements and social sciences. For each of these categories, this paper mentions a brief future outline. This review study indicates mainly three types of future development directions for NFS methodologies, domains and article types: (1) NFS methodologies are tending to be developed toward expertise orientation. (2) It is suggested that different social science methodologies could be implemented using NFS as another kind of expert methodology. (3) The ability to continually change and learning capability is the driving power of NFS methodologies and will be the key for future intelligent applications.

https://romisatriawahono.net/lecture/rm/survey/softcomputing/Kar%20-%20Neuro%20Fuzzy%20Systems%20-%202014.pdf

Review Article: Applications of neuro fuzzy systems: A brief review and future outline

Research highlights? The proposed framework can identify cause and effect relationships among strategic objectives of strategy map through processing of the expertise and knowledge of senior managers. In this process, the integrated structure is introduced for the macro level balanced scorecard. And in addition to the mathematical modeling of cause and effect relationships, a decision support system could be presented that may increase the efficiency of the balanced scorecard management system. The Balanced Scorecard (BSC) is a widely adopted performance management framework first introduced in the early 1990s. More recently, it has been proposed as the basic for a strategic management system. Strategy mapping is the most important task in building a Balanced Scorecard system. Strategy mapping is the process for visually making cause and effect relationships between all possible strategic objectives in an organization. The process for building and constructing a strategy map is a human centric activity which could be considered as the combination and integration of all knowledge and preferences of the managerial boards. From the view point of strategic decision making in an organization, the process for building a strategy map could be viewed in a general body of a unified group decision making context. If we see the strategy map, as a structural modeling framework for making the cause and effect relationships among the strategic objectives, it is possible to deploy Decision Making Trial and Evaluation Laboratory (DEMATEL) as a framework for structural modeling approach subject to the problem. The DEMATEL method gathers collective knowledge to capture the causal relationships between strategic criteria. The model is especially practical and useful for visualizing the structure of complicated causal relationships with matrices or digraphs. Generally speaking, because in building any strategy map, the assigned preferences between the objectives are not crisp necessarily, and experts' domain knowledge could be extracted in a fuzzy environment, then the extended fuzzy DEMATEL is proposed to deal with the ambiguities inherent of such the judgments.

A Fuzzy DEMATEL framework for modeling cause and effect relationships of strategy map

This research provides a comparison between the performances of TSK (Takagi, Sugeno, Kang)-type versus Mamdani-type fuzzy inference systems. The main motivation behind this research was to assess which approach provides the best performance for a gyroscope fault-detection application, developed in 2002 for the European Space Agency (ESA) satellite ENVISAT. Due to the importance of performance in online systems we compare the application, developed with Mamdani model, with a TSK formulation using three types of tests: processing time for both systems, robustness in the presence of randomly generated noise; and sensitivity analysis of the systems' behaviors to changes in input data. The results show that the TSK model perform better in all three tests, hence we may conclude that replacing a Mamdani system with an equivalent TSK system could be a good option to improve the overall performance of a fuzzy inference system.

A Comparison of Mandani and Sugeno Inference Systems for a Space Fault Detection Application

Dynamic multi-criteria decision making (DMCDM) is an emerging subject in the decision-making area and in the last decade the challenge to consider time as an important variable has become important. Some frameworks already exist in this area but when compared with other types of decision-making models, DMCDM needs more work to be applicable in real industrial problems. In this work we extend a dynamic spatial-temporal framework, designed to deal with historical data (feedback), to address the problem of considering future information/knowledge (feed-forward). The main objective is to enrich dynamic decision-making models with explicit knowledge (existing historical data) and tacit knowledge (e.g. expert predictions) in time-evolving problems, such as supplier selection. Considering supplier-predicted information for future situations (e.g. investments in capacity) and, simultaneously, learning from historical data can help a company to find less risky and consistent alternatives. The proposed model is suc...

Dynamic MCDM with future knowledge for supplier selection

There are a few popular business excellence models that provide standard criteria against which an organization can measure its performances. European Foundation for Quality Management (EFQM) is the most popular one. The organizational self-assessment process is an admissible system in the area of Total Quality Management (TQM). Most specialists concur to the description of self-assessment that is presented by the European Foundation for Quality Management (EFQM). However, the current self assessment methods in EFQM model have some drawbacks and problems which are scoring in these methods influenced by experts’ judgment and thus, are subjective. Furthermore, these methods cannot consider the empirical investigation and expert knowledge in scoring and also they cannot convert uncertain and imprecise data (linguistic variables) to crisp data. Since Artificial Intelligence models such as Fuzzy Logic can solve the uncertainties and complexity in assessment system, a new assessment system for EFQM evaluation will be designed using fuzzy logic. The proposed assessment system can provide an effective and precise scoring, simultaneously considering knowledge and experience of experts and assessors. The results showed that the new comprehensive developed model is more valid and acceptable and the experts verified the model for assessing based on EFQM in practice. The developed model was used in a case study and results drawn out from it were evaluated from distinctive viewpoints.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID1935118_code1586957.pdf?abstractid=1934607&mirid=1&type=2

Assessment System Based on Fuzzy Scoring In European Foundation for Quality Management (EFQM): Business Excellence Model

Strategic planning is expressly significant for organization's success and competitive advantage making in an increasingly competitive business environment. Implementation of applicable strategies plays an important role for organizations' success. Balanced scorecard is a suitable tool for designing operative strategies. However, one of the balanced scorecard difficulties is the selection in strategic plans' performance. In this issue paper, was demonstrated a model for selection and ranking of strategic plans in Balanced Scorecard using Topsis method and Goal Programming model. So first using the view and consensus of organization's managers and experts' opinions, measures of four perspectives and objectives are settled in BSC. And then using experts' opinions and taking the relative importance of decision makers' opinions into consideration, by using Goal Programming model and Topsis method, the implementations of strategic plans are selected in BSC model. The results are revealed that the introduced methods are more reliable and acceptable and the experts were verified the model for selecting of strategic plans in BSC in operation. The initiated methods were used in a study and derived results from it were analyzed from various points of view. In this article Initiative is called strategic plans.

Javad Jassbi

Papers

A Fuzzy DEMATEL framework for modeling cause and effect relationships of strategy map

A Comparison of Mandani and Sugeno Inference Systems for a Space Fault Detection Application

Dynamic MCDM with future knowledge for supplier selection

Assessment System Based on Fuzzy Scoring In European Foundation for Quality Management (EFQM): Business Excellence Model

Using Topsis Method with Goal Programming for Best Selection of Strategic Plans in BSC Model