Journal Of Industrial Engineering International
Volume:19 Issue: 1, Winter 2023

The companies in the aviation industry require exact scheduling and operation due to their complex and costly activities. The aircraft routing problem (ARP) which meets all of the requirements related to maintenance operations and achieves the minimum costs is among the significant issues for an airline. Solving the ARP includes creating all of the routes and defining aircraft maintenance inspections. The present study aims to review and categorize the recent research on ARP and maintenance operation. To this aim, four significant categories including type of model, maintenance and repair factors, disruption and robustness, as well as objective function and solution approach were defined. Based on the literature review, the integrated study of the airline schedule steps provides better results than the multi-stage review. In addition, defining the combined framework of different maintenance factors generates a more accurate schedule to control the maintenance requirements. Further, applying multiple hybrids meta-heuristic approach leads to significant results.

A significant issue for businesses is the risks connected to the production system, which can be related to people and their expertise, the technology being utilized, or the environment, endangering their productivity, continuity, and development. Risk assessment procedures are necessary to determine the most likely source of an undetected hazardous event that prevents the system from performing its function. This paper proposes a probabilistic methodology to evaluate the risks associated with a combed spinning workshop factory inside a textile company. It is a hybrid strategy based on the BN and the MADS-MOSAR methodology. In this proposal, we employ the MADS model to pinpoint risk sources from both human and environmental sources. The MOSAR approach, however, has some quantitative drawbacks. To get past this issue, we also present the integration of BN. The results of the experiments show that the suggested technique is competitive and more effective for managing and reducing risks; all types of enterprises can use it.

Repair machines play a critical role in military, communication, industrial, and manufacturing settings. This study investigates the performance of a system that utilizes repair machines with human operators, employing Copula's attributes for estimation. The research focuses on a serial system composed of two subsystems, each consisting of two active components running in parallel. Both subsystems are manned by two human operators and assigned two repair machines for operation and maintenance, where the repair machines are considered failure-prone systems. The system experiences partial and complete malfunction during operation: Partial malfunction lead the system into reduced capacity mode, and a complete malfunction resulting in system failure. The research employs the technique of supplementary variable and transforms of Laplace to establish and solve the governing differential equations corresponding to schematic system's diagram. Performance models for the system such as profit, MTTF, availability, sensitivity of MTTF and reliability are numerically validated and presented through tables and graphs. These findings are highly valuable for evaluating performance, identifying ideal system designs, and developing workable maintenance plans. The research contributes to enhancing system performance, increasing production output, and improving revenue mobilization in various application domains.

In this paper, according to the discussion of improving the safety of nuclear power plants (NPPs) according to reports and findings of Fukushima accident, a model for the economic analysis of a NPP with a higher level of safety in an electricity power market is provided. Therefore, a solution to determine the balance between safety and economy to deal with station black-out (SBO) accident in a pressurized water reactor (PWR) nuclear power plant is presented. A supply function equilibrium (SFE) that takes into account carbon tax in the power market is used to calculate the profit of each power generation firm. A hierarchical innovative approach is used to make decisions about improving the safety of NPP. In this method, breakeven point (BEP) is used as the decision criterion to compare the safety improvement costs and profit of NPP in the power market. This method is used to add an emergency diesel generator (EDG) and a mobile heat exchanger to a NPP that examines the impact of investment costs and profits. The result shows that with the addition of an EDG to the NPP, the BEP of investment costs and net profit of the NPP is one month later. Finally, it can be suggested to the investor of the NPP to add EDG to improve safety, so that the implementation of this proposal leads to a slight increase in payback period, but greatly reduces core damage frequency (CDF) of NPP reactor in SBO accident.

 Wastewater treatment has been a challenge for beverage companies in recent years which has led them to establish specific units to purify the expired returning items before agricultural uses or disposal. This issue has never been studied from the perspective of inventory and production management. This paper proposes an inventory formulation in the case of Behnoush beverage company in Iran to determine the replenishment cycle and the optimal selling price of items when: (a) items deteriorate continuously and have their specific expiration dates, (b) a proportion of items that are expired are moved to the company and after the process of wastewater treatment, and (c) a trade credit period is offered to the buyer to make encouragement for ordering in larger quantities. Optimality conditions for the total cost function are elaborated. Thereafter, numerical experiments are adopted for validation. Eventually, managerial implications are outlined and findings of the study are summarized.

The problem of allocation of financial resources in projects is one of the most important problems of mathematical optimization. Incorrect allocation of financial resources can lead to project failure, increased costs, and reduced profitability. The importance of this issue has led to the modeling of a financial resource allocation problem for sustainable projects under uncertainty in this article. A fuzzy programming method was used to control model parameters and GSSA, GA, and SSA algorithms were used to solve the model. In the mathematical model, the goal was to optimize the objective function consisting of predicted return, investment risk, and project sustainability. Mathematical calculation results showed that meta-heuristic algorithms have high efficiency in achieving optimal solutions in a short time. so that the average time to solve them was less than 10 seconds. Also, the calculation results showed that increasing the uncertainty rate leads to increasing the value of the objective function and creating a distance from the optimal point. This is due to increasing costs and decreasing profits in sustainable projects. Finally, usage the TOPSIS method, the ranking of solving algorithms was done, and the GSSA algorithm was the most efficient algorithm among other algorithms with a desirability weight of 0.846.