نرم افزار فازی FMEA برای بهبود فرایند خرید در یک بیمارستان دولتی

Failure mode and effects analysis (FMEA) is one of the well-known techniques of quality management that is used for continuous improvements in product or process designs. While applying this technique, determining the risk priority numbers, which indicate the levels of risks associated with potential problems, is of prime importance for the success of application. These numbers are generally attained from past experience and engineering judgments, and this way of 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. In this study, a fuzzy-based FMEA is to be applied first time to improve the purchasing process of a public hospital. Results indicate that the application of fuzzy FMEA method can solve the problems that have arisen from conventional FMEA, and can efficiently discover the potential failure modes and effects. It can also provide the stability of process assurance.

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 and 3, 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.

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 implementation of fuzzy FMEA method to the purchasing process for medical supplies in a public hospital, several corrective actions were recommended. For 20 of the 28 failures observed improvement suggestions were made while for the remaining 8 failures no improvement was suggested. Some of these recommendations which were related particularly with the creation of medical supplies data bank, other fields of personnel, operations, communications, and documentation were realized during the project activity period. For the remaining failures an implementation plan was made to be activated in the future. Since the plan required a long time (about 6 months) the project could not be completed within the period of study. Therefore, at this stage, the average improvement in the RPN could not be clearly identified. However, with the implementation of all measures, it is expected to have a decline about 20% in procurement time, and 15% in time spent by the workforce. Besides, competition will increase among suppliers and the purchases will be made more transparent. Results indicate that the application of fuzzy FMEA method can solve the problems that have arisen from conventional FMEA, and can efficiently discover the potential failure modes and effects. It can also provide the stability of product and process assurance. This study is the first authentic example of how fuzzy FMEA approach might be helpful to the management processes. Similarly, in all other management processes in manufacturing and service sectors it is quite possible to use this technique successfully.