* Starting from Need* Evolution of the Toyota Production System* Further Development* Genealogy of the Toyota Production System* The True Intention of the Ford System* Surviving the Low-Growth Period

Toyota production system : beyond large-scale production

Multi-Criteria Decision Aid (MCDA) or Multi-Criteria Decision Making (MCDM) methods have received much attention from researchers and practitioners in evaluating, assessing and ranking alternatives across diverse industries. Among numerous MCDA/MCDM methods developed to solve real-world decision problems, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) continues to work satisfactorily across different application areas. In this paper, we conduct a state-of-the-art literature survey to taxonomize the research on TOPSIS applications and methodologies. The classification scheme for this review contains 266 scholarly papers from 103 journals since the year 2000, separated into nine application areas: (1) Supply Chain Management and Logistics, (2) Design, Engineering and Manufacturing Systems, (3) Business and Marketing Management, (4) Health, Safety and Environment Management, (5) Human Resources Management, (6) Energy Management, (7) Chemical Engineering, (8) Water Resources Management and (9) Other topics. Scholarly papers in the TOPSIS discipline are further interpreted based on (1) publication year, (2) publication journal, (3) authors' nationality and (4) other methods combined or compared with TOPSIS. We end our review paper with recommendations for future research in TOPSIS decision-making that is both forward-looking and practically oriented. This paper provides useful insights into the TOPSIS method and suggests a framework for future attempts in this area for academic researchers and practitioners.

Review: A state-of the-art survey of TOPSIS applications

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This paper proposes a fuzzy TOPSIS method based on alpha level sets and presents a nonlinear programming (NLP) solution procedure. The relationship between the fuzzy TOPSIS method and fuzzy weighted average (FWA) is also discussed. Three numerical examples including an application to bridge risk assessment are investigated using the proposed fuzzy TOPSIS method to illustrate its applications and the differences from the other procedures. It is shown that the proposed fuzzy TOPSIS method performs better than the other fuzzy versions of the TOPSIS method.

Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment

Failure mode and effects analysis (FMEA) is a risk assessment tool that mitigates potential failures in systems, processes, designs or services and has been used in a wide range of industries. The conventional risk priority number (RPN) method has been criticized to have many deficiencies and various risk priority models have been proposed in the literature to enhance the performance of FMEA. However, there has been no literature review on this topic. In this study, we reviewed 75 FMEA papers published between 1992 and 2012 in the international journals and categorized them according to the approaches used to overcome the limitations of the conventional RPN method. The intention of this review is to address the following three questions: (i) Which shortcomings attract the most attention? (ii) Which approaches are the most popular? (iii) Is there any inadequacy of the approaches? The answers to these questions will give an indication of current trends in research and the best direction for future research in order to further address the known deficiencies associated with the traditional FMEA.

Review: Risk evaluation approaches in failure mode and effects analysis: A literature review

Technical Note: A note on A multiple-vendor single-buyer integrated inventory model with a variable number of vendors

This paper deals with the analysis of a controller used to synchronize two parallel belt conveyors in a packaging plant. A first conveyor carries the products, while the second delivers the packages. The insertion is obtained by a proper mechanical action. The control system is based on a ‘hybrid’ fuzzy logic controller, whose parameters are optimized by using an advanced ‘operational’ genetic algorithm. ‘Hybrid’ means that a conventional fuzzy logic controller is integrated with a set of special rules needed to solve particular situations characterizing the system. An important constraint is given, since the physical structure of the existing control system is to be kept unchanged. It is shown that the controller efficiently governs the belt conveyors when: (a) the distances between goods and the relative packages become higher than a certain value; (b) the performance of the electrical engine deteriorates during working time; and also (c) interference phenomena occur between consecutive good-package couples. Copyright ©2003 John Wiley & Sons, Ltd.

Fuzzy logic controller in a packaging plant

In this paper, we consider the continuous review (S − 1, S) policy with complete backordering, deterministic and constant lead-time, and with a Poissonian lead-time demand. Moreover, we take into account two different expressions of the total expected cost depending on the customer-service criterion adopted. First, we approximate the Poissonian lead-time demand with a well-suited Gaussian random variable. Although this system can be easily solved with a simple algorithmic approach, it is interesting to be aware of the direct analytical functional relationship between the optimal value of the decision variable and the parameters of the model. Hence, the second step consists in providing some approximated closed-form minimum-cost solutions for both cost models considered under a Gaussian lead-time demand. An extensive numerical study is finally shown to characterise the precision achieved by the approximations developed.

Approximated closed-form minimum-cost solutions to the (S − 1, S) policy with complete backordering

Process planning plays a fundamental role within modern industrial facilities in that it is devoted to select the manufacturing processes and parameters and the sequences that are needed to convert a part from the initial to the final form. Evaluating the quality of a process plan from both a technological and an economic perspective becomes vital. Indeed, a valid process plan not only ensures the required quality of manufactured parts, but also reduces the production cost. The present chapter is aimed at presenting the essential concepts and the historical evolution of the process planning approaches, starting from a general point of view and then introducing the most important and recent real-world applications. In addition, it introduces the fundamental aspect regarding the interactions between process planning and production scheduling, pinpointing the strengths and weaknesses of the available proposed solutions. Doing so, it addresses students, researchers as well as practitioners.

Process Engineering and Optimization

Conventional controllers for the packaging industry are often based upon look-up tables, where past experiences help practitioners to establish the expected outcomes, corresponding to several combinations of inputs, or on the adoption of Proportional, Integrative and Derivative controllers (PIDs), that are widely used due to their intrinsic robustness in a wide variety of operating conditions The first method grants fast and readily available responses, but, at the same time, requires great amounts of computational resources, whereas PIDs are difficult to set up and necessitate continuous adjustments In both cases the controlled systems are rather unstable and show unpredictable behavior, mainly due to numerous and random disturbances this results, making the control unable to deal with sudden changes



In the last decades Fuzzy Logic (FL) have emerged as a way to help overcome most of the disadvantages of the traditional control techniques This aspect has been further improved by researchers with the aid of some well known Artificial Intelligence (AI) techniques, such as Genetic Algorithms (GAs) and Artificial Neural Networks (ANNs), and with the adoption of computer-aided simulation tools, that provide significant help during the set up and fine tuning of the controller Recent literature is now available that deals with the adoption of FL hybrid controllers for packaging processes, addressing their particular aspects, and presenting noteworthy results and practical implications Whereas some good theoretical applications of the Fuzzy Logic Controllers (FLCs) to packaging processes are available, there is still a noticeable lack of real-world implementations, mainly due to the great number of variables that may govern the processes themselves and that require long and complex tweaking stages The present work presents a comprehensive review of the most interesting theoretical and practical implementations of the FLCs to the packaging processes, with the aim of pinpointing the strengths and the weaknesses of each proposal and giving a clear and up-to-date report of the state of the art


Keywords:

packaging;
fuzzy logic;
fuzzy logic controllers;
bottling;
overfilling;
electronics

Marco Frosolini

Papers

Technical Note: A note on A multiple-vendor single-buyer integrated inventory model with a variable number of vendors

Fuzzy logic controller in a packaging plant

Approximated closed-form minimum-cost solutions to the (S − 1, S) policy with complete backordering

Process Engineering and Optimization

Fuzzy Logic Control in the Packaging Industry