Fuzzy FMEA application to improve purchasing process in a public hospital
Graphical abstract
Highlights
► Determining the risk priority numbers in FMEA is of prime importance for the success of application. ► Classical risk assessment sometimes leads to inaccuracies and inconsistencies during priority numbering. ► Fuzzy logic approach is preferable in order to remove these deficiencies in assigning the risk priority numbers. ► A fuzzy-based FMEA is to be applied first time to improve the purchasing process of a public hospital. ► Fuzzy FMEA can efficiently discover the potential failure modes and effects and provide the stability of process assurance.
Introduction
Today's hard economical conditions, in which health companies operate, force the managers of these companies to use various scientific methods and new technological equipments on the way to attain more productive usage of their resources. Particularly the situations such as increasing costs, limited budget, and severe competition require development of planning and supervisory activities. Among health companies the public hospitals are the foundations which are directly affected from these circumstances.
Public hospitals are also the organizations who work with limited resources. The allocative inefficiency is a fundamental flaw in the public hospitals and these inefficiencies drain the limited public resources allotted for health care [1]. The more rationally they manage their supplies, the less negative outcomes of deficiencies or corruptions exist. Extensive usage of medical technologies requires considerable amounts of resources to be consumed at temperate levels and where they are needed. It is clear that if equipment/material purchases are realized without making an evaluation of requirements and getting cooperation of the hospital management, then the capacities and the qualities of these purchased items could be so far away from meeting the hospitals real needs [2]. That is why the purchasing process is very important in hospitals and should be improved continuously.
Process improvement plays a key role in business process management for every organization as well as for health organizations. It is a series of actions taken to identify, analyze and improve existing processes within an organization to meet new goals and objectives. These actions often follow a specific methodology or strategy to create successful results.
Understanding processes so that they can be improved by means of a systematic approach requires the knowledge of a simple kit of tools or techniques. The effective use of these tools and techniques requires their application by the people who actually work on the processes, and their commitment to this will only be possible if they are assured that management cares about improving quality. Managers must show they are committed by providing the training and implementation support necessary.
The tools and techniques most commonly used in process improvement are: DRIVE (define, review, identity, verify, execute), process mapping, process flowcharting, force field analysis, cause and effect diagrams, pareto analysis, brainstorming charting, matrix analysis, spc, etc. Failure mode and effect analysis (FMEA) is one of these techniques. In the following sections, the FMEA based on fuzzy approach is to be applied first in a public hospital to improve its purchasing process. The paper is organized in such a way that FMEA and fuzzy FMEA is introduced in Sections 2 Failure mode and effect analysis (FMEA), 3 Fuzzy approach to FMEA, literature review is given in Section 4, purchasing process in hospitals is discussed in Section 5, and the fuzzy FMEA application is given thoroughly in Section 6. The paper ends with concluding remarks.
Section snippets
Failure mode and effect analysis (FMEA)
FMEA is an analytical technique that combines the technology and experience of people in identifying foreseeable failure modes of a product or process and planning for its elimination [3]. It is widely used in manufacturing industries in various phases of the product life cycle and is now increasingly finding use in the service industry.
Traditional FMEA uses a risk priority number (RPN) to evaluate the risk level of a component or process. The RPN is obtained by finding the multiplication of
Fuzzy approach to FMEA
Fuzzy logic is a form of multi-valued logic derived from fuzzy set theory to deal with reasoning that is approximate rather than precise. The fuzzy logic variables may have a membership value of not only 0 or 1, but a value inclusively between 0 and 1. In fuzzy logic the degree of truth of a statement can range between 0 and 1 and is not constrained to the two truth values {true (1), false (0)} as in classic propositional logic [6]. Thus, the fuzzy logic provides a basis for approximate
Literature review
A number of investigations have been conducted to enhance the FMEA methodology using artificial intelligence techniques. Recently, many studies have been published in technical fields where FMEA was used together with fuzzy sets. For example, Xu et al. [15] implemented a fuzzy logic-based FMEA in diesel engine systems. Guimaraes and Lapa [16] applied fuzzy FMEA to PWR chemical and volume control system. The authors also applied a pure fuzzy logic system to FMEA of an auxiliary feedwater system
Purchasing process in hospitals
There is a whole process that hospitals must go through before they purchase one piece of hospital equipment. They do this process for several reasons and it can involve many different departments of the hospital. They have to make sure that every piece of equipment they buy is up to the standards of the technology they are using at the time in order to give the best and most accurate information to their patients that they can. They must also stick within their budget in order to keep the
The hospital and its purchasing problems
The proposed method was applied in the purchasing department of a public hospital located in Istanbul. The purpose of the study was to improve the hospital's purchasing process by examining the process itself and by determining the measures which reduce the procurement (lead) times and costs and eliminate the burden of unnecessary work. As it provides the necessary inputs for other processes, the improvement of the purchasing process would bring a positive impact on all the following processes,
Conclusion
Traditional FMEA determines the RPN by finding the multiplication of factor scores that are converted from the probability or degree of problem occurrence without considering the relative importance of factors. This study applied fuzzy theory to eliminate the conversion debate by directly evaluating the linguistic assessment of factors to obtain RPN by assigning relative weighting coefficient.
Fuzzy FMEA was applied first time to improve purchasing process in a public hospital. After the
Mesut Kumru is an Asc. Prof. of Industrial Engineering at Dogus University of Istanbul. He received his BSc, MSc, and PhD degrees in Industrial and Production Engineering majors from the universities of Boğaziçi and Istanbul. He has spent 25 years of his professional life in national (ECA, Işıklar) and international (Bosch-Siemens-Profilo) groups of industrial companies, where he undertook several management responsibilities at every level from supervising up to general management. During his
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Mesut Kumru is an Asc. Prof. of Industrial Engineering at Dogus University of Istanbul. He received his BSc, MSc, and PhD degrees in Industrial and Production Engineering majors from the universities of Boğaziçi and Istanbul. He has spent 25 years of his professional life in national (ECA, Işıklar) and international (Bosch-Siemens-Profilo) groups of industrial companies, where he undertook several management responsibilities at every level from supervising up to general management. During his private sector career he conducted around 30 technical researches and directed more than 50 project assignments for manufacturing companies in different sectors. He has also published lots of technical and scientific papers. He contributed to the Turkish government as members of national advisory board, and state planning organization on the matters of quality management. Dr Kumru's research interests lie mainly in quality and production management. He is founder of Turkish Quality Association. He has been active in several national and international associations (TOBB, IASTED, EOQ, etc.).
Pınar Yıldız Kumru is an Ast. Prof. of Industrial Engineering at Kocaeli University of İzmit. She holds BSc degree in Industrial Engineering from the university of Kocaeli; MSc and PhD degrees in Production Management from Istanbul University. She has actively worked in academy and conducted various researches and projects on different subjects, mainly on methods engineering, ergonomics, and management psychology. She is the author of many publications and owns several memberships in professional organizations.