International Journal of Industrial Engineering: Theory, Applications and Practice

Adjusting The Factors Affecting The Internal Rate of Return on Investment in Production-Sharing Oil Contracts to Stabilize The Interests of The Investor

Neda Ghavidast — 2024-06-17

The 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.

Development of The Reliability Assessment in Preventive Maintenance of Heat, Ventilation, and Air Conditioning (HVAC) Systems for The Production of Pharmaceutical Product

Adam Ikhwan Zulkiflee — 2024-06-17

The support system of heat, ventilation, and air conditioning (HVAC) in manufacturing plants plays an important role in the optimum efficiency of the production system. Failure to support adequate HVAC on the production floor will cause production defects, stoppage time, unplanned machine downtime, and other related issues. These issues highly affect those products that require dedicated temperature, pressure, and humidity, such as production clean rooms, food industries, and pharmaceutical products. Thus, this study aims to develop and apply the specific reliability assessment in an investigation of HVAC, focusing on the production of pharmaceutical products. In this study, the selected statistical quality tools have been applied in the evaluation and prediction of the HVAC failure and maintenance process. To ensure suitable tools and methods will be applied, a systematic approach has been developed consisting of six steps towards effective maintenance of the HVAC system. The main purpose of the application quality tools such as check sheet, Pareto chart, scatter plot, and probability plot was to evaluate the historical failure data and then to predict the potential future failure through analysis of Mean Time Between Failure (MTBF) in steps 1 to 4. To ensure the developed approach successfully implemented the Failure Mode and Effects Analysis (FMEA) in step 5, the corrective action plan was suggested in step 6. Once the systematic approach of HVAC preventive maintenance had been successfully developed, it was then implemented in the selected production floor of the pharmaceutical industry. The execution of this developed systematic approach to predicting the HVAC resulted in an increase in the total MTBF from 529.50 minutes to 778.23 minutes. It showed an improvement of 47% after the implementation of the developed systematic approach. The obtained results showed that reliability assessment was important for the optimization of production efficiency.

Digital Twin-Oriented Collaborative Optimization of Process Planning and Scheduling in A Flexible Job Shop

Zhaoming Chen — 2024-06-17

Process planning and scheduling are two crucial components in flexible manufacturing systems. To address the challenge of information interaction and sharing during the process planning and scheduling stage of parts, a digital twin-oriented approach is proposed. The objective is to optimize the maximum makespan while accommodating fluctuations in the job shop site. Firstly, in the process planning stage, an enhanced genetic algorithm is employed to generate multiple near-optimal process routes. These routes are coded using a four-level coding system, enhancing the efficiency of the planning process. Then, in the production scheduling stage, a hybrid particle swarm optimization algorithm is constructed, considering the characteristics of multi-process routes and the status of shop production resources and production systems. To improve local search ability, various neighborhood structures are utilized. Finally, the proposed method is evaluated through production example simulations and compared with genetic algorithm and particle swarm optimization. The results demonstrate that this method has a quicker convergence rate, shorter execution time, and higher computation precision, which is not only remarkable but also practical for addressing the collaborative optimization of process planning and scheduling in discrete manufacturing systems.

Retail or Commissioned Live-Streaming? Mode Choice of A Platform Supply Chain Considering Consumers’ Preferences

Juehao Cheng — 2024-06-17

''live-streaming + e-commerce'' mode emerged as time required. In this paper, we aim to investigate the manufacturer’s pricing and mode choice of cooperation with a live streamer in a dual-channel live-streaming supply chain consisting of a single manufacturer, a KOL(Key Opinion Leader) live streamer, and a live-streaming platform, considering different consumers’ preferences. We depict two scenarios for the KOL streamer, retail live-streaming and commissioned live-streaming modes, in the presence of a manufacturer's self-live-streaming and investigate the optimal mode choice with the Stackelberg game. The paper discovers that under the commissioned live-streaming mode, the price of KOL live-streaming is positively (negatively) correlated with the commission ratio (consumers' preferences for the manufacturer’s self-live-streaming) and lower than that under manufacturer self-live-streaming under a low commission ratio (a high consumers' preferences for manufacturer’s self-live-streaming). In both scenarios, the KOL live-streaming’s sales effort is consistently lower than that of the manufacturer's self-live-streaming channel. Additionally, the consumer's sensitivity coefficient, the trust degree, the impact of KOL streamers, and the proportion of impulsive consumers are positively correlated with both channels' price, sales effort, and profit.

Intelligent Demand Forecasting Approaches for Spare Parts in The Energy Industry

Yu-Chung Tsao — 2024-06-17

In 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.

Managing The Online Channel by Coordinating A Third-Party Logistics and Service Provider Along with A Dual-Channel Retailer

Mohannad Radhi — 2024-06-17

This 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.

A Systematic Analysis of Supply Chain Risk Management Literature: 2012-2021

Xiaoxin Zhu — 2024-06-17

In order to secure supply chains (SCs), researchers and policy makers need to be abreast of developments in supply chain risk management (SCRM). This study selected frequently cited papers of WoS from the last 10 years, performing quantitative visualization analysis to establish the current trends within the field. Further attention was paid to those studies that focused on the impact of COVID-19. This study used a keyword timeline and clustering analysis map to establish the main research directions between 2012 to 2018, as well as the perspectives from which SC optimization was studied from 2018 to 2021. The key journals and research institutions for SCRM are established, as well as the key categories that the published literature falls under. Cluster analysis shows which areas in the published literature have the most references. Finally, the study establishes the direction of current trends within SCRM, as well as its understudied areas.

Efficient Material Handling: A Novel Adaptive Gating System for Small and Irregular Parts

Mohan Arumugam — 2024-06-17

In the automotive industry, efficient handling of small and irregular components is imperative for production optimization. Traditional methods involving labor or robotic systems can lead to increased costs. The research introduces an innovative, dynamic gating system, integrating a camera module with computing intelligence to process images and orient parts effectively in linear feeders. Theoretical and experimental results validate the most preferred orientation, with orientations 1 and 2 from group 1 identified as the optimum resting positions. The use of both the Markov model and a hidden Markov model in trap module design yields a robust outcome, effectively attaining the necessary part orientation. The dynamic part feeding system is optimized for frequencies of 45 and 50 Hz with trap angles of 30° from the experimental study. The study quantifies efficiency gains, demonstrating that the proposed system outperforms manual or robotic methods. This study offers a quantitative and comprehensive solution for assembling and packaging small and irregular components in the automotive sector.

Unmanned Aerial Vehicle Path Planning Using Water Strider Algorithm

Madhusudhanan Sampath — 2024-06-17

This paper presents a multi-agent optimal path planning and obstacle avoidance using a water strider algorithm (WSA) based on Sequential Convex Programming (SCP). The outcome is to find optimal collision-free trajectories. The best collision-free trajectories with minimum control effect is needed in the multi-agent route planning technique, which makes use of a centralized WSA algorithm that can guide drones over congested environments while avoiding both static and moving objects. By applying convex constraints on the drones' such as acceleration, velocity input and jerk, the feasibility of the trajectory is ensured. The optimal trajectory path is iteratively created using SCP and followed by WSA. The outcome guarantees the correctness of the linearization. Since the optimization is centralized, it is possible to find a feasible collision-free path, and the results are validated pre-determined formation. It is shown that the WSA algorithm scales with O³(n), where n is the number of drones.

Tourism Route Association Recommendation Algorithm Based on Changes of User's Interest Characteristics

Min Fang — 2024-06-17

In order to improve the ability to recommend tourism routes and increase tourist route satisfaction. This article designs a tourism route association recommendation algorithm based on changes in user interest characteristics. This article provides information on the distribution of tourist routes and Constructs the topology structure of tourism routes. The paper utilizes a multi-block fusion matching method to construct an optimal feature allocation model, Using optimized spatial clustering fuzzy functions to mine preference feature models and Introducing a joint distribution density function to solve the correlation recommendation of tourist routes. The experimental results show that when using this algorithm, the accuracy of the sample set is improved by 1.6% compared to the accuracy of the test set, and the recall rate is improved by 2.9%. Compared with the traditional algorithm, the proposed algorithm has the highest confidence and the best regression effect, which indicates that the proposed algorithm can effectively improve the recommendation efficiency.

Network Structure and Realization Path of Urban Green Sustainable Development Based on Improved Social Network Analysis Hybrid Method

Xiaoping Bai — 2024-06-17

Telecommunication is one of the essential necessities of everyday life. In India, the telecommunications sector has seen a significant increase in the day-to-day. Telecommunications service companies hold data about their customers, and crisp graphs are used to depict these records. Examining and selecting the best mobile phone service providers (MPSPs) based on operational restrictions will help determine the best MPSPs. The analysis of MPSPs may be regarded as a difficult decision-making issue. The aim of this article is to provide an outline to examine the performance of MPSPs and the selection of the best MPSP for customers in India. The statistical data were obtained from the Telecom Regulatory Authority of India between April 2019 and March 2021. A novel approach for cosine similarity measures (CSM) among hesitancy fuzzy graphs (HFG) and estimating the certified repute scores of the experts by determining the ambiguous information of hesitancy fuzzy preference relations (HFPRs) and the regular cosine similarity grades from one separable HFPR to some others. And consider “objective” and “subjective” information given by experts. According to CSMs, we define the Laplacian energy of an HFG. This research provides a solution to a decision-making problem by applying the newly developed cosine similarity measure and the Laplacian energy of hesitancy fuzzy graphs. The ranking order of all alternatives and the best one is determined by calculating the cosine similarity between each alternative and the ideal alternative. Finally, an illustrated example is provided to show the applicability of the proposed approach to the decision-making problem as well as its effectiveness.

Decision Making Approach for Best Mobile Phone Service Provider Selection Using Laplacian Energy and Cosine Similarity Measures of Hesitancy Fuzzy Graph

Rajagopal Reddy Nallapareddy — 2024-06-17