Austenitic 316LVM stainless are widely used in biomedical industry in particular medical surgical applications, and implant materials. In biomedical applications, especially implants used in the body are exposed to tribological conditions that cause wear behavior. Wear behavior of Implants fabricated by using these materials related to the surface conditions. One of the important processes influencing the surface properties used in fabricating process of implant is machining operation. For this reason, the effect of machining parameters and condition on the surface properties of this material and eventually altering the wear response is the focus of this current research. In this paper, dry milling operations of Austenitic 316LVM under various parameters were presented. The surface roughness, microhardness, microstructure are the examined surface integrity characteristics in this study. The effect of generated characteristics resulting from machining on wear resistance is measured using pin-on-disc test. It was revealed that cutting speed and feed has notable effect on surface roughness and strain hardening of the specimen. Increased strain hardening generally results in decreased wear resistance while increased surface roughness results in increased wear resistance.

Vortex shedding from an oscillating disc with a chamfered tip is investigated. The experiments are performed using a high-speed Particle Image Velocimetry (PIV) system with 160Hz frame acquisition frequency. Six full cycles are recorded with a total of 1999 recordings, i.e. 333 velocity measurements resolving a single cycle. The 175-mm-diameter disc oscillation frequency was 0.5Hz within a 20mm displacement in water. Dynamic image masking is performed to remove the disc shape from the PIV raw images, using rigid object tracking and image stabilization techniques. This implies a coordinate transformation and allows the investigation of flow field results with respect to the disc, as if it were stationary. This allows the use of statistical analysis and phase-locked averaging. The results indicate that the vortex formation and shedding from-cycle-to-cycle is very stable and predictable. The chamfered disc tip geometry has great influence in the vortex dynamics: When the motion is towards the chamfered side, a big, attached trailing vortex is present on the flat side; and when the motion is reversed towards the flat side the big trailing vortex is shed off outwards from the center, and a shear layer with a 45° orientation is formed. This means the asymmetric disc tip geometry generates a net force for the complete cycle.

Usage of UHSS (ultra high-strength steels) had increased in recent years, automobile Body in White -BIW- manufacturers had faced the challenge of choosing between two types of currents for resistance spot welding equipment. The objective of this work is to compare the effects of welds obtained from both AC and MFDC (alternate current – AC – power source and medium frequency constant current one – MFDC) machines on mechanical performance. Two different welding equipment had been used for making joints between as-delivered 22MnB5 and DP600 steel sheets. The micro-hardness results, tensile shear (TS) and cross tension (CT) tests of resistance spot welded (RSW) joints between as - delivered (22MnB5) and double phase (DP600) steels for both AC and MFDC process are detailed. According to the results, comparatively lower hardness values were observed in the weld metal and heat effected zones of the welded samples obtained by MFDC technology compared to AC technology. The positive effect was observed in the strength and elongation values of the samples welded with MFDC technology according to AC technology. When the CT and TS test results were evaluated, more than 5% improvement is observed on welded samples with MFDC technology. The originality of this paper presents a comparative study of joint performance properties effect for both AC and MFDC process on dissimilar joints between as-delivered 22MnB5 and DP600.

In recent years, as a type of smart materials, shape memory polymers (SMPs) are being popular in industrial applications. Thermoplastic shape memory polyurethane (SMPU), which is a type of shape memory polymers, is become interesting because of the properties which are easily moulding and reusability. As commonly in commercial thermoplastic materials, it is expecting that using injection moulding process for shaping permanent shapes of the parts moulded by SMPU. In this study, the part quality was investigated by using short shot, air traps, and part weight in permanent shape of injection moulded SMPU specimens. The relationship among injection pressure, melt temperature, mould temperature, packing pressure, and time, cooling time and short shot, air traps and part weight were inspected experimentally. The design of experiment was prepared by using Taguchi’s L27 orthogonal array and experimental data was evaluated by ANOVA. While the effect of injection pressure, and melt temperature on short shot was found to be significant statistically, air traps were affected by injection pressure and mould temperature. It was found that the effective parameters on part weight are injection pressure, melt temperature, mould temperature and packing pressure, respectively.

One of the most important failures that occur during the forming of laminated composite materials is shear failure. Interlaminar shear strength is examined to determine this mechanism of damage. In this study, bending test via the short beam method was applied to thermoplastic composite laminates with two different compositions. It was aimed to analysis on the effects of the glass fiber architecture types on shear properties of the thermoplastic composite laminates. Both types of composite laminates have 3 mm thickness, the matrix element is Polypropylene and the reinforcing element is glass fiber. The first material has a fiber ratio of 60% and a continuous fiber stacked at 0/90 in its structure. The fiber content of the second material is 38% and it contains both chopped and woven continuous fiber. The interlayer shear properties of two kinds of composite laminates containing reinforcement elements in different types were compared. In addition, failure situations were examined by performing macro imaging. The shear strength of the hybrid reinforced composite laminate was higher than the composite material with high continuous fiber weight ratio.

Natural rubber-based composite mixtures (NRC) are widely used as commercial material in vehicle tires, shock absorbers, suspension system components, and various engineering applications due to their superior performance properties. In addition to the extremely severe conditions of the working environments of rubber-based materials, it also contains a serious fire safety problem. In this study, thermal, flame retardant and mechanical properties of rubber composite mixtures prepared with the addition of carbon black (CB) and intumescent flame retardant agents (IFR) with different particle sizes to be used as raw materials in air suspension systems were investigated. The effect of filler materials and flame retardants used on NRC was investigated using thermal analysis (TGA), combustion tests, mechanical tests, SEM, and microscopic studies. It was observed that the thermal stability and flammability of the composites depend on the network structure, the content, and the type of the additive in the mixture obtained. Particle size reduction has a significant role on reducing NRCs flammability while also increasing their mechanical properties.

The focus of this article is on the line balancing work planned on the assembly line of a Dishwasher Factory. The main motivation is to make the assembly line more stable by grouping similar jobs and to increase the number of dishwashers produced per shift. In addition to these basic objectives, this study aims to rearrange the number of operators, optimize work-stock area and balance the man power at the stations. We propose a novel integer programming model that takes into account the location selection of stations, elevators and robots and the decisions of assigning jobs and workers to stations and use a commercial solver to solve the problem exactly. In the light of the outputs obtained from the solution of the problem, the current system and the improved system results were compared. First, the increase of dishwasher production capacity under current operational guidelines was evaluated and then the effect of grouping jobs on cycle time was evaluated. Based on the results of the sensitivity analysis, different results were proposed to optimize the current tempo, cycle time and number of workers. The results indicate that the number of workers can be reduced by 36%, while the number of dishwashers produced per shift can be increased by up to 52%, when all other inputs of the problem are fixed. Compared to the current practice, in the solution proposed to the manufacturing firm, the number of stations opened with similar jobs grouped was reduced by 68%, the number of fields that could be used by the stations was kept the same, the number of workers was reduced by 10% and the cycle time was improved by 4.34 seconds and the number of machines produced per shift increased by 43%.

The sustainability impact and reporting results of air transport have become important for societies. In this field, the Global Reporting Initiative presents the reports and databases of many sectors in chronological order. Nowadays, airports all over the world transparently present their sustainability results to the public with a sense of responsibility. In this respect, measuring the sustainability performance of airports, determining the targets, and making the necessary improvements become more of an issue. In this study, efficiency analysis of 30 international airports included in the comprehensive sustainability database of the Global Reporting Initiative was carried out using the Data Envelopment Analysis (DEA). In this context, common inputs and outputs affecting sustainability of airports were determined and sustainability performance measurement model was developed. The relative efficiency scores of the airports were found with the input oriented CCR method by using the developed model. Thanks to the results, inefficient airports were identified, and necessary improvements were presented to improve sustainability levels.

Random Forests is a widely used machine learning algorithm for classification and regression problems from different domains. Although they are generally accurate, their interpretability is low compared to their building blocks: single decision trees. Using the fact that each member of a Random Forest is a decision tree, we propose different set partitioning formulations to extract interpretable if-then rules from Random Forests. Our experiments on well-known classification and regression datasets show that the original set partitioning model formulation significantly reduces the number of rules while keeping the accuracy at acceptable levels. We also propose a modification to the problem's objective function, which aims to reduce the number of extracted rules further. We observe a further reduction in the number of extracted rules while the accuracy values stay nearly the same. Although the set partitioning problem is NP-hard, we obtain optimal results for most datasets within twenty minutes.

Warehouses are crucial in supply chain management. They are used to distribute and store products. In this study, we optimize storage location assignment decisions in a warehouse managed by a manufacturing firm. A mathematical model is introduced to solve the nonlinear mixed integer optimization problem (NLMIP), i.e., the Storage Location Assignment Problem (SLAP) by using historical data from warehouse management system (WMS). Clustering and ABC analysis is conducted based on the number of times two items are picked together and the picking frequency of items, respectively and embed the results into our optimization model. Also, a greedy heuristic is developed to solve SLAP of the firm. According to obtained output, the distances between filled slots and the I/O point of the current system and our proposed solution are compared in order to see the improvement in the system, and an improvement of up to 49.99% is observed.

The assembly line balancing problem (ALBP) contains some constraints which are cycle time/number of stations and precedence relations between tasks. However, due to the technological and organizational limitations, several other restrictions, such as linked tasks, incompatible tasks, station, and resource constraints, can be encountered in real production systems. In this study, we evaluate the effect of these restrictions on ALBP. For this purpose, a Constraint Programming (CP) model is proposed. The objective of the model is to minimize the number of stations for given cycle time (Type-1 problem). We investigate the solution quality of the proposed CP model according to the mixed-integer programming (MIP) and ABSALOM in terms of the several performance measurements such as the number of proofing optimal solution, number of the optimal solution, number of the best solution, relative gap between the solution with the optimal solution and average total solution time. Furthermore, the proposed approach is tested on the literature test instances, and the comparison results between models are reported. Although assignment restrictions increase the complexity of the problem, numerical experiments demonstrate that CP is an effective and high-quality solution method in solving ALBP.

One of the important keys of both regional progress and economic development is the energy issue. As the demand for energy increases with the growing population, countries are developing various policies regarding the supply, distribution and sustainability of energy in planning energy investments. At this point, investments for renewable energy (RE) sources that will provide the least damage to the environment and can be transferred to future generations are increasing considering the climate change and greenhouse gas emission risks. The aim of the study is to analyze RE resources in TR83 region from a multi-criteria decision making (MCDM) perspective by presenting an application for evaluating RE investments. For this purpose, using the CRITIC based Gray Relational Analysis (GRA) approach, it was ensured that the RE sources in TR83 region were evaluated and ranked according to their performance. According to the results, it is observed that the province which is the best in terms of RE investments at the regional level is Samsun.

Turkish furniture industry has a view of mainly workshop-type, small-scale businesses mostly working with traditional methods. By both office and employment levels in furniture group of products, in the Aegean region Izmir, Denizli and Manisa are among the provinces where most employees are employed. In these provinces there are smaller firms with six persons and employment levels below the average in Turkey in terms of number of employees per business. In order to most effectively take advantage of the labor force, physical environmental conditions must be adapted to human. Employees in unsuitable conditions cannot be efficient as they do not feel comfortable.
This research work in the enterprises engaged in the production of furniture was conducted to determine the ergonomic adequacy of work and physical environmental conditions by employees. For this purpose, a total of 400 employees from the small-scale enterprises engaged in the production of furniture in Denizli, Izmir and Manisa Provinces were included in the research. In the study, the assessment of ergonomic adequacy of the enterprise by employees was measured by their responses to 51 Likert type sentences. In this study, Principal Component Analysis of dimensionality reduction methods was used.

In financial data mining, stock index movement direction prediction is a challenging classification problem, since stock index is affected by many economic and political factors. The accurate prediction of this problem is of interest to many researchers as it can serve as an early recommender system for short-term financiers. This study aims to predict daily upward or downward movement direction of Borsa Istanbul 100 (XU100) index with the aid of supervised machine learning algorithms based on classification. Problem we deal with includes whether on a specific day the XU100 index fall into up bucket or fall into down bucket. For this purpose, the multiple logistic regression and K-nearest neighbors algorithm models are fitted using independent variables whose effect on BIST100 index movement direction was statistically significant. Lastly, the out-of sample predictions are compared with the actual movements in the stock market. Performances are measured not only with accuracy but also other statistical metrics. According to the results obtained, logistic regression analysis achieves better predict performance with 81% accuracy opposed to K-nearest neighbors algorithm on XU100 data over the given time period.

Balancing nurse workload while scheduling outpatient chemotherapy appointments under uncertainty is a challenging problem. In this study, a two-stage stochastic mixed-integer programming model is proposed for setting appointment times of patients and assigning patients to chairs and nurses without distorting the workload balance among nurses. The uncertainty in pre-medication and infusion durations is considered. The objective function of the model minimizes the expected weighted sum of patient waiting time and nurse overtime. Computational experiments are conducted based on data from an outpatient chemotherapy unit of a large hospital. The trade-off between the two competing criteria of the study is investigated. The relationship between the numbers of chairs and nurses in the clinic with the performance measures is examined. The benefit of considering uncertainty is assessed by calculating the value of stochastic solution.