Bir kamu hastanesinde yemekhane hizmet sürecinin iyileştirilmesi

Neredeyse tüm hastanelerin bilinen problemlerinden birisi, farklı düzeylerde de olsa, yemeklerin hastalara soğuk ulaşmasıdır. Problemin çözümü süreç iyileştirme kapsamında ele alınabilmektedir. Bu çalışmada, bir kamu hastanesinde daha önceden yapılmış bir anket sonucu ortaya çıkan bu sorun, süreç iyileştirme analizi yapılarak çözülmeye çalışılmakta, iyileştirme önerileri ortaya konmaktadır. Araştırmada, tanımlayıcı ve açıklayıcı bilgileri elde etmek için tarama modeli kullanılmıştır. DMAIC metodolojisi takip edilerek etki-neden analizleri yapılmış, yemek dağıtım süreleri gözlemlenmiştir. Yemek dağıtım sürelerini olumsuz etkileyen darboğazlar üzerinde durularak yemekhane servislerinin daha kısa sürede gerçekleştirilebilmesi için Hizmet Kalite Standartları da gözetilerek öneriler ortaya konmuştur.One of the common problems that exists at different levels in almost all of the hospitals, is serving the meals to patients cold. The problem could be solved by process improvement approach. In this study, the problem, which emerged as an outcome of a previously conducted survey, is to be solved in a public hospital and improvement suggestions are put forward. In the research, a scanning model is used in order to attain descriptive and explanatory information. Following the DEMAIC methodology, cause and effect analyses were conducted; times for meal serving were observed. Focusing on the bottlenecks that affect negatively the meal serving times, improvement suggestions were made to realize the serving time shorter by taking into account the Quality Service Standards

Revenue management for returned products in reverse logistics

Returned products take a considerable part in logistics. Recovering the returned products is one of the management issues of manufacturing companies. As an element of reverse logistics, product recovery encompasses several options, i.e., remanufacturing, repair, refurbishing, cannibalization and recycling, which are classified based on the degree of disassembly and the quality level of the recovered product. Difference in quality levels of recovered products draw different prices in the secondary markets. This situation gives rise to revenue management, i.e., to set the prices of recovered products of different quality levels such that the total revenue is maximized. One of the decision problems is the location of collection and inspection points in order to minimize the cost of reverse distribution. In our framework, we include preliminary inspection, that requires physical checking etc. and needs no substantial investment, at the collection points, and detailed inspection at the remanufacturing facility.In this paper, we modify the pricing model of Subrata Mitra to maximize the expected revenue from the recovered products. Numerical example is included for illustration.Doğuş Üniversitesi; TÜBİTA

Analytic hierarchy process application in selecting the mode of transport for a logistics company

SUMMARY As a multi-criteria decision-making (MCDM) method, the analytic hierarchy process (AHP) has been used considerably to solve hierarchical or network-based decision problems in socio-economic fields. Following an in-depth explanation of the transport function in logistics and an overview of the MCDM methods, the AHP model is employed in the paper for a logistics company in selecting the most suitable way of transportation between two given locations in Turkey. The criteria used in the selection of transportation modes are identified as the cost, speed, safety, accessibility, reliability, environmental friendliness, and flexibility. Several cost parameters (transportation, storage, handling, bosphorus crossover) are incorporated into the decision-making process. The application is carried out in instructional character. The results of the study indicate that the railway transportation, which is not widely used in Turkey, is also an alternative and suitable means of transportation. Copyright © 2013 John Wiley & Sons, Ltd

Assessing the visual quality of sanitary ware by fuzzy logic

Quality control systems focus on maintaining standards in manufactured products. To improve the homogeneity of batches received by final users and to detect manufacturing defaults, a visual control stage is integrated into production line before the packing operation. At this stage, the products are inspected, mostly by human eye, for their obvious external defects; e. g., chips, cracks, scratches, holes and pitting, lumps, spots, notches, and glazing. This task is often referred to as visual inspection which is important to categorize the final products into quality-constant batches. Prototypes are of invaluable help while inspecting the visual attributes of products. Visual quality of products is assessed with respect to these standard units and some quality ratings are made there on the results. However, assessing visual quality is somewhat an ambiguous and troublesome work. Therefore, it will be helpful to utilize a decision making technique, such as fuzzy logic, to facilitate and improve the process. This paper addresses first to the significance of visual inspection and assessment of visual quality of industrial products, and second, gives a unique application of visual quality assessment of vitreous china ceramic sanitary wares by using fuzzy logic method

Using artificial neural networks to forecast operation times in metal industry

This study was conducted in an auto spare parts production plant where the biggest bottleneck in managing the enterprise is the lack of fulfilling the requisitions of the customers on time. The main reason for the delay is the absence of operation time data valid for the required parts ordered with different specifications. For preparing effective schedules and for eliminating the bottleneck, the factory needs to use reliable operation time data for each part produced. An artificial neural network (ANN) approach was used for this purpose, and its forecasting performance was compared with that of multiple linear and nonlinear regression models. Based on the statistical analyses, the ANN approach outperformed the regression models and is found to be more reliable in forecasting the operation times

Analysis of employee satisfaction in an automotive spare parts manufacturing company

Kumru, Mesut (Dogus Author) -- Conference full title: 37. Yöneylem araştırması ve Endüstri Mühendisliği Ulusal Kongresi; Yıldız Teknik Üniversitesi, İstanbul, 5-7 Temmuz 2017Otomotiv yan sanayiinin lider firmalarından birisinde çalışan memnuniyeti incelenmiştir. Bu maksatla bir anket düzenlenmiş, bu anketle çalışanların işyerindeki fiziksel çalışma ortamından, yaptıkları işlerden, iş arkadaşlarından, çalıştıkları şirketten, amirlerinden, genel şirket yönetimi ve eğitim programlarından memnun olup olmadıkları konusunda bilgi edinilmeye çalışılmıştır. Sözü edilen organizasyonel faktörlere ilaveten kişisel faktörler olarak yaş, cinsiyet, hizmet süresi, statü ve eğitim durumu incelenmiştir. Söz konusu değişkenlerin çalışan memnuniyeti düzeyine etkileri araştırılmıştır. Çalışanların sözü edilen faktörlerden memnuniyet düzeyleri ile demografik özelliklerinin ilişkisi parametrik olmayan ki-kare testiyle incelenmiştir. Bu çerçevede oluşturulan dokuz hipotez test edilmiştir. Ayrıca, yapılan iş ve çalışılan şirketle ilgili bazı hususlar yedi ana faktörle ilişkilendirilmeye çalışılmış, örnek regresyon bağıntıları ortaya konulmuştur

A fuzzy ANP model for the selection of 3D coordinate - measuring machine

Kumru, Mesut (Dogus Author)The analytic network process (ANP) method is normally used to determine the relative weights of a set of evaluation criteria when ranking the competing alternatives in terms of their overall performance. It has the ability to deal with interdependent relationships among the criteria. Since the fuzzy logic approach provides more accuracy on judgments, the fuzzy extension of the ANP method enables the decision-maker to use uncertain human preferences as input information in the decision-making process. The fuzzy ANP enhances the potential of the conventional ANP for dealing with imprecise and vague human comparison judgments. In this work, a fuzzy ANP method is introduced to present a performance analysis on a specific machine tool selection problem. Unlike conventional fuzzy ANP applications, the proposed approach here is to be applied comprehensively for a sophisticated machine selection case in a company. Different from the machine tool selection studies so far done, machine hardware and software are to be discussed together in the selection process. It is used for the selection of a 3D coordinate-measuring machine for a die manufacturing company. The results indicate more accurate and reliable decision making in machine tool selection problem

A balanced scorecard - based composite measuring approach to assessing the performance of a media outlet

In an attempt to overcome massive challenges to survive in today's global and volatile marketplace, companies are adopting newer management systems to clarify their vision and strategy and translate them into action. The balanced scorecard (BSC) is one such approach which is gaining significant interest, especially within the small and medium size enterprises. This paper describes a BSC-based composite measuring approach to performance measurement and illustrates how the approach was used by a media outlet in Turkey as part of strategic policing initiative. In the paper, first, a BSC framework was adapted, and then a composite measure was developed thereon to assess the performance of the organization with regard to its strategic business objectives. The scorecard-based composite measure was built around a vision to create superior growth of aggregate value through outlet operations. It was found that by using the suggested framework, it is possible to identify and measure the cause-and-effect relationship of using an effective operations strategy, and to assess its impact on the company's competitive advantages. This research exercise confirms the validity and usefulness of the proposed methodology and offers managerial insights and guidelines for similar implementations

Neural networks and search for minimum defectiveness in molding operation in ceramic industry

Kumru, Mesut (Dogus Author) -- Conference full title: 2011 International Symposium on Innovations in Intelligent Systems and Applications (INISTA 2011) Istanbul, Turkey, 15 - 18 June 2011This study is to be conducted in a ceramics production plant where the highest product defectiveness occurs in the molding shop of the plant. There are a number of factors that affect the amount of product defectiveness. The purpose is to search for a set of factor treatment conditions which provide the minimum defectiveness performance in the shop. Artificial Neural Network (ANN) method was used to realize the purpose. Based on the statistical analysis, the ANN approach is found to be reliable in predicting the amount of defectiveness that depends on various factors.TUBITAK, IEEE

Calendar-based short-term forecasting of daily average electricity demand

Kumru, Mesut (Dogus Author) -- Conference full title: International Conference on Industrial Engineering and Operations Management (IEOM), 2015 3-5 March 2015, Hyatt Regency, Dubai, United Arab Emirates.Short-term electricity demand forecast becomes more and more important due to recent deregulation of electricity market in Turkey. It is affected mainly from several factors that are working days, weekends, feasts, festivals, and temperatures. In the study, contribution of these factors to the consumption is to be analyzed and modeled with nonlinear (quadratic) regression models. First, the variation in Turkey's daily electricity consumption for the years of 2012 and 2013 is determined with respect to actual weather temperatures and calendar events. Then, nonlinear regression models are constructed separately for the demand function of weekends, weekdays, public holidays (feast and festivals), and for the total daily averages. The models are tested on the actual calendar data of the year 2014 for its twelve months period. Mean absolute percentage errors are calculated and compared for each of the regression models. The results indicate that the calendar-based short-term forecasting model slightly outperforms the noncalendar-based forecasting model, and seems more reliable in forecasting the short-term electricity demand.ASQ; IEEE; BOEING; Emirates; Lawrence Technol Univ; Saudi Aramco; Informs; PROLIM; SIEMENS; Univ New Brunswic