International Journal of Industrial Engineering: Theory, Applications and Practice
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Intelligent Demand Forecasting Approaches for Spare Parts in The Energy Industry
No full textIn this study, two intelligent demand forecasting approaches are used to forecast the spare parts demand in the energy industry. In the first approach, a stacked generalization-based demand forecasting technique that combines traditional time-series forecasting and machine-learning methods is developed. In the second approach, external information (EI) is incorporated into the first one. Thus, the stacked generalization-based demand forecasting technique is used as a base model, and the EI is used to focus on predicting the peak demand; consequently, significant forecast errors can be minimized. A case study of a natural gas liquefaction company is then considered to test the performance of these methodologies. Our results show that the proposed techniques perform significantly better than the previous methods. Compared with the mean absolute scaled error and relative geometric root mean squared error of the company’s forecasts, our intelligent demand forecasting approaches yield a 40.07% (36.81%) and 2.07% (3.40%) increase in butterfly-valve demand forecasting (spiral wound gasket) when no EI is used, and a 57.78% (60.41%) and 5.73% (7.36%) improvement with EI, respectively
Exploring the Design Guidelines of Large Screen UI for Optimal Viewing Experience on Smart TV
No full textWith the prevalence of large-screen smart TVs, viewing experiences are becoming more interactive. This technological advance makes an increase in information density and diverse layouts. This study aims to derive ergonomic design guidelines for TV UI to optimize the viewing experience. Fifteen subjects participated in the main test, performing tasks consisting of visual navigation and remote manipulation according to twelve different alternatives. The experimental variables were selected as screen size, information quantity and layout. The dependent measures were collected on performance time, visual cognitive satisfaction and manipulation satisfaction. The results revealed that screen size, information quantity, and layout had significant effects on visual satisfaction. Larger screens with more information enhanced visual cognitive satisfaction. Screen size and information quantity influenced on manipulation satisfaction. Meanwhile, information quantity and layout had greater impacts on user performance. This research provides appropriate design guidelines for smart TV UI and practical implications for product developers
Adjusting The Factors Affecting The Internal Rate of Return on Investment in Production-Sharing Oil Contracts to Stabilize The Interests of The Investor
No full textThe financial system of production-sharing contracts has more complications in comparison with other oil contracts, especially production participation contracts. The financial system and the conditions governing the payment and repayment of production-sharing contracts can be modeled at various times during the implementation of these contracts, and by using this modeling, the profitability of the plan for the parties of the contract can be evaluated, and an optimal decision can be made based on the results of the modeling In the research literature, the economic analysis of oil production-sharing contracts in the middle stages of contract implementation has not been done or very little has been done from the perspective of the investor. In this paper, economic mathematical modeling of oil production-sharing contracts with the aim of maximizing the investor's internal rate of return is presented. In this model, the data is derived from a real contract that has been delayed for approximately 30 months, as well as payment and repayment forecasts for the next 56 months. To optimize the model, we have simulated monthly payments and repayments were generated by observing their minimum and maximum values in 2000 times and each time, the rate of return was calculated, and the optimal payment and repayment amount was determined. Results specify that if the contract has been delayed, the investor can improve the internal rate of return by managing the timing of payments
Managing The Online Channel by Coordinating A Third-Party Logistics and Service Provider Along with A Dual-Channel Retailer
Get PDFThis paper considers traditional and online stores under the context of a dual-channel retailing system. Fully refunded returns are permissible in both forms: same-channel and cross-channel. We examined three different coordination strategies that may form between the retailer and a third-party logistics and service provider. The provider was tasked to manage the online store’s orders through transaction-based fees, flat-based fees, and gain-sharing contracts. For each of those strategies, we found the online store’s optimal pricing policy and the seasonal fee, if applicable. The performance ratings of the partners under the different strategies were compared, and the managerial insights were provided using analytical as well as numerical analysis. It was found that the retailer is always more profitable under the flat-based fee strategy compared to the gain-sharing strategy, while the provider was almost always more profitable under the latter strategy. Moreover, a low rate of return encouraged the retailer to have more independence by implementing the transaction-based fee strategy, while a high rate pushed the retailer to have more logistical involvement and support through the implementation of either the flat-based fee or gain-sharing strategies
Integrated Fuzzy Multi-Criteria Decision Making Application within An Environmental Evaluation Framework: A Case Study in Türkİye
No full textThe selection process of eligible suppliers in supply chains entails numerous challenges under rapidly evolving conditions. Environmental considerations in public discourse, competitive market structures, and emerging technological capabilities influence the decision-making procedures. Rather than the conventional criteria of cost and service, different criteria have more recently been taken into consideration. In this study, presenting a Turkish case study, environmental management, environmental agility and environmental technology dimensions and the criteria related to these dimensions are defined. A fuzzy SWARA-BWM method was implemented in an integrated way to cope with the supplier selection problem. Different scenarios were created and benchmarked. The results of the study indicate that environmental agility is the prominent dimension, while the most significant criterion is delivery speed. The optimal supplier alternative among the four alternatives was identified as . This study was carried out to contribute to the examination and modeling of supply chain management issues
Two-Step Methodology for Statistical Anomaly Detection and Prediction Using XGBoost Regression in Blower Motor Vibration Time Series Data
No full textAnalyzing the vibration of blower motors in industrial sites to detect and predict anomalies is important for increasing operational efficiency and enhancing predictive maintenance. Existing methods risk malfunctions due to over-sensitivity, and deep learning approaches in particular require long periods of data for training and are difficult to maintain. This research is divided into two phases: diagnostic analysis and predictive analysis. The first phase, diagnostic analysis, utilizes the PELT (Pruned Exact Linear Time) algorithm and SPC (Statistical Process Control) techniques to identify vibration data points with abrupt pattern changes and outside the normal operating range. The second step, predictive analysis, utilized the XGBoost Regression algorithm to identify patterns in the vibration data to predict potential failures and their timing. The algorithm used in the study provides computational efficiency and high prediction accuracy, which can compensate for the shortcomings of existing methods. The study also presents a methodology that can effectively detect and predict anomalies in blower motors and similar mechanical facilities in industrial environments
A Clear Tool Path optimization for Rough Pocket Machining with Contour-Parallel Offset Toolpaths
No full textThe context of this study is the rough machining of pockets using Contour-Parallel Offset (CPO) trajectories. This requires either minimizing the toolpath or increasing the feed rate because the objective during the roughing stage is to minimize machining time. Increasing the spacing between contours to a value close to the tool diameter minimizes the total toolpath length. However, this can result in material leftover between passes in the corners. A lot of work has been done to eliminate uncut areas after machining. Rounded loops added to the continuous CPOs proposed by several researchers and integrated into the CAM software (Mastercam) provide the most reliable solution that can maintain the feed rate at its maximum value during direction changes. However, the size of these loops penalizes the gain already achieved by maintaining the feed rate. Therefore, it is evident to conduct a detailed study to make the latter more optimized. In this paper, we propose a generalized algorithm for any polygon. It utilizes new formulas and adds an optimized loop at any point where uncut areas appear. This loop challenges the best existing methods aimed at minimizing machining time during rough pocket machining with CPO toolpaths, as it is designed in a highly optimized manner and ensures overlap in the corners between passes in any situation. For the validation of this new method, comparisons were made with the best methods found in the literature through simulations. Additionally, several tests conducted within Mastercam and with other methods, as well as a real implementation, have confirmed the effectiveness and advantage of the proposed method compared to the best existing rough pocket machining methods. The fact that this method offers a highly optimized toolpath and maintains the actual feed rate at its maximum due to the rounded profile of the loop suggests that rough pocket machining with CPO toolpaths could become the best solution
CONTEXT-TREE APPROACH FOR MONITORING THE MULTI-WAY CONTINGENCY TABLES-BASED PROCESSES WITH DEPENDENCE BETWEEN NEIGHBORHOOD CELLS
No full textIn recent years, some statistical process monitoring (SPM) approaches have been used to control contingency table-based processes. The common assumption in this research is that the Neighborhood cells of the contingency table are temporally independent. This paper develops a new approach based on the Context-Tree method and Kullback-Leibler (KL) statistic to monitor the multi-way contingency tables by considering the dependence between Neighborhood cells in Phase II. The proposed approach is evaluated by using some simulation studies. In addition, the efficiency of the proposed approach has been approved using other sensitivity analyses in some numerical examples by contingency tables with more rows and columns and contingency tables with more categorical variables. Results show that proposed statistics have suitable performance in detecting the out-of-control condition under different shifts in a multi-way contingency table
CIRCULAR SUPPLY CHAIN MANAGEMENT: CONTENT ANALYSIS WITH SPECIFIC DRIVERS AND BARRIERS
No full textThe entire process of producing, distributing, and delivering goods and services to consumers in the supply chain has a significant impact on the environment. The transition towards Circular Supply Chain Management (CSCM) is imperative for addressing contemporary sustainability challenges. This study attempts a systematic exploration of the key barriers and drivers influencing the adoption of circular practices within supply chains by using content analysis and a systematic literature review. This paper highlighted the importance of CSCM adoption. The outcome of the study is relevant as it gives a framework of barriers and drivers for the CSCM implementation by a force field analysis. Various critical factors are assumed to define hypotheses as the basis of further research. This review has great significance for CSCM practitioners, academicians, managers, and policymakers. By recognizing the barriers and the drivers, organizations can embark on a transformative journey toward circular practices in their supply chains
EVALUATING THE WORK DESIGN READINESS FOR INDUSTRY 4.0 BASED ON PERSONAL CHARACTERISTICS OF PRODUCTION WORKERS: Work Design Readiness for Industry 4.0
No full textThe design of work is a crucial consideration for production workers in terms of performance, satisfaction, and motivation. This aspect has garnered increasing attention in research, particularly with the rise of automation and the transition to Industry 4.0-enabled smart factories. Work design is influenced by both internal and external performance-shaping factors (PSFs). Internal factors include human, machine and task elements and traits, which HR specialists can structure to enhance efficiency and productivity in manufacturing. External PSFs, such as physical, psychological, social and organizational factors, also play a significant role in shaping production work. This study aims to understand the impact of personal characteristics of production workers in an automated factory. The research findings are extrapolated on an Industry 4.0 framework to establish a productive work design. Data collection is conducted through a quantitative survey, and non-parametric analysis of variance tests are employed to assess significant relationships. The results indicate a better perception of the pace of operations (µ = 4.19) and feedback (µ = 4.47) among elder workers. Additionally, educated workers express significant perceptions regarding external PSFs such as supervision (µ = 4.39), health and safety (µ = 4.25), job rotation (µ = 3.91) and pay and welfare (µ = 3.58). Aspiration, motivation and organizational commitment emerge as crucial work design attributes for experienced and married workers. These findings contribute to understanding the structure of modern work design in the context of Industry 4.0, aiming to enhance performance and worker productivity. The study proposes an advanced Industry 4.0 work design framework, empowering HR specialists to develop effective strategies and optimize work distribution