Nilgün Fığlalı

Investigation of Ant System parameter interactions by using design of experiments for job-shop scheduling problems

In recent years, one of the most important and promising research fields has been metaheuristics to find optimal or near-optimal solutions for NP-hard combinatorial optimization problems. Improving the quality of the solution or the solution time is basic research area on metaheuristics. Modifications of the existing ones or creation of hybrid approaches are the focus of these efforts. Another area of improving the solution quality of metaheuristics is finding the optimal combination of algorithm control parameters. This is usually done by design of experiments or one-at-a-time approach in genetic algorithms, simulated annealing and similar metaheuristics. We observe that, in studies which use Ant Colonies Optimization (ACO) as an optimization technique; the levels of control parameters are determined by some non-systematic initial experiments and the interactions of the parameters are not studied yet. In this study, the parameters of Ant System have been investigated on different sized and randomly generated job-shop scheduling problems by using design of experiments. The effects and interactions of the parameters have been interpreted with the outputs of the experiments. Referring to the statistical analysis it is observed that none of the interactions between the Ant System parameters has a significant effect on makespan value. A specific fractional experimental design is suggested instead of the full factorial design. Depending on the findings from the benchmark problems it will be a reliable approach to use the suggested design for saving time and effort in experiments without sacrificing the solution quality.

Image processing-aided working posture analysis

OWAS method is adapted to an integrated software as a prototype.It operates completely computer-aided with the help of image processing techniques.That models performance is high while robust recording conditions can be settled.Necessity of expert analyst is eliminated.The model will support the common use of OWAS in industry. Musculoskeletal Disorders (MSDs) rank among the commonest health problems both in the frequency of concurrency and in the money spent on these disorders, which mainly stem from poor working posture it also negatively affects employees in terms of job productivity, life quality, and both physical and social activities. Analyzing and improving working postures with scientific methods provides significant contributions in the field of controlling job performance and decreasing MSDs. OWAS (Ovako Working Posture Analyzing System) is one of the methods for analyzing working postures and can be applied to very diverse areas successfully. In this study, a prototype of integrated software, which is based on image processing techniques, was developed (I-OWAS), and the performance of the model was presented. I-OWAS begins with separating the video film into frames, producing OWAS codes belonging to working posture in each frame, and then classifying the images according to risk categories. Despite OWAS being a successful method for analyzing working postures, it requires an expert analysis. Also the manual analyzing process is so laborious and time consuming. I-OWAS provide the computer support for the manual coding stage and eliminates the need for an expert analyst; hence, the method can be widely used in industry.

Using Owas in Automotive Subsidiary Sector: A Case Study

Musculoskeletal Disorders (MSDs) that lead to important health problems and the depletion of social resources are the most common drawbacks affecting the working population. MSDs that are at the top of the list showing the expenditures for all disorders, and affecting the job efficiency, life quality and physical and social functions of a worker in a negative way, is generally due to the poor working postures. There are several methods to identify the poor working postures that cause Musculoskeletal Disorders (MSDs) and financial burdens to the economies along with serious health problems for workers. OWAS (Ovako Working Posture Analysing System), one of these methods, depends on the observational analysis of work movements especially in physically demanding works. In this study, the working postures in tire raw materials production process are analyzed with OWAS method and some suggestions are made about the possible improvements to eliminate the poor working postures.

Application of lean production techniques in the manufacturing industry

Lean production is producing in a short time, cheaply and error-free, while satisfying customer demands. The aim is to decrease waste and to increase effectiveness by using lean production techniques. The mould room was selected as the pilot application area. For this purpose, several studies were conducted: 1) to determine and decrease the idle capacity and time waste in new mould production, maintenance and repair moulds; 2) to decrease the waiting time and material flow; 3) to diminish supply costs; 4) to turn the system into a FIFO system by decreasing the cycle time. At the end of the study, the efficiency was increased by 10%, the cycle time was decreased by 20% and the distance over which materials flow was decreased by 60%. The implementation of the designed production cells freed 120m2 of space. 8,000 hours per year are gained with the elimination of the non-value adding stations.

Expert system application for prioritizing preventive actions for shift work: shift expert

Introduction. Shift patterns, work hours, work arrangements and worker motivations have increasingly become key factors for job performance. The main objective of this article is to design an expert system that identifies the negative effects of shift work and prioritizes mitigation efforts according to their importance in preventing these negative effects. The proposed expert system will be referred to as the shift expert. Methods. A thorough literature review is conducted to determine the effects of shift work on workers. Our work indicates that shift work is linked to demographic variables, sleepiness and fatigue, health and well-being, and social and domestic conditions. These parameters constitute the sections of a questionnaire designed to focus on 26 important issues related to shift work. The shift expert is then constructed to provide prevention advice at the individual and organizational levels, and it prioritizes this advice using a fuzzy analytic hierarchy process model, which considers comparison matrices provided by users during the prioritization process. An empirical study of 61 workers working on three rotating shifts is performed. After administering the questionnaires, the collected data are analyzed statistically, and then the shift expert produces individual and organizational recommendations for these workers.

Implementation of reliability-centred FMEA in a cable cutting process

Reliability is an important criterion affecting the automobile buying decision of customers. One of the most important components in automobiles is the cables ensuring the electricity current. Even the smallest breakdowns in these cables create crucial problems. Because of that, it is aimed to work with zero error in the production phase. In this study, the objective is the determination of possible and present errors in the cutting phase of electric cables and avoidance from these errors before they occur. In this regard, failure mode and effects analysis (FMEA) methodology is used, which is an analysis done for prevention and identification of all possible error types. Preventions found by FMEA have been implemented and high risk priority numbers (RPNs) are reduced in a cable cutting process. The study shows that significant improvement in possible errors can be ensured with the use of FMEA.