工业工程与管理

The Traveling Salesman Problem (TSP) is one of the most well-known and studied optimization problems in the field of operations research and computer science. It involves finding the shortest possible route that visits a set of cities and returns to the origin city. The Flying Sidekick Traveling Salesman Problem (FSTSP) is a fascinating extension of the classic TSP. In the FSTSP, the salesperson is equipped with a "flying sidekick," which can transport them between pairs of cities. This adds an intriguing dynamic to the problem, as the salesperson must decide when to use the sidekick for aerial travel and when to stick to conventional road travel. In this article, we explore the application of a simulated annealing heuristic to tackle the Flying Sidekick Traveling Salesman Problem. We'll delve into the problem's background, the simulated annealing approach, and how this powerful optimization technique can be harnessed to reach effective solutions for the FSTSP.

Materials selection is a fundamental aspect of engineering design and plays a pivotal role in determining the performance, durability, and costeffectiveness of a product or structure. The process of selecting the right materials for a particular application involves evaluating multiple criteria, such as mechanical properties, cost, environmental impact, and availability. To make informed decisions in material selection, engineers and researchers employ various methods and tools. In recent years, there has been a growing interest in applying advanced mathematical approaches, such as Fermatean fuzzy hybrid aggregation operators, to enhance the optimization of material selection processes. This article explores the concept of material selection, the challenges it poses, and how Fermatean fuzzy hybrid aggregation operators can be applied for maximum optimization.

In the realm of power plant maintenance, the role of human factors is increasingly acknowledged as critical. Human Factors Engineering (HFE) aims to optimize system performance by considering human capabilities and limitations. Yet, the fundamental prerequisite for successful HFE implementation lies in the ability of personnel to adjust and adapt. This article delves into the significance of adaptability in power plant maintenance before the execution of Human Factors Engineering. Power plant maintenance involves a complex interplay of human actions, technology, and environmental factors. Maintenance tasks demand precision, adherence to protocols, and quick decision-making abilities. Amidst this complexity, adaptability stands as a pivotal trait for maintenance personnel. Adaptability encompasses the capacity to modify strategies, skills, and approaches in response to varying conditions and challenges encountered during operations.

To launch or keep a medical device on the US market, FDA pre-approval or continued approval is required. After product approval, the FDA routinely conducts surveillance inspections of medical device companies. The present study looks at issues related to medical device CAPA and the associated costs of remediation for non-compliance with the FDA. This study delves into the costs and issues related to medical device companies for failing to meet FDA expectations. The study will examine the issues that the FDA has with medical device CAPA and suggestions on how to remedy them. This information served as the basis for identifying and examining methods to help reduce or eliminate FDA CAPArelated findings for medical device companies to reduce failure related costs and improving the understanding of CAPA requirements and process efficiencies to help reduce the risk of an FDA finding.

Noncompliance with FDA regulations and failure of medical device quality have resulted in substantial additional costs to a medical device company. Non-routine quality events such as major FDA observations, recalls, warning letters, and consent decrees, along with associated warranties and lawsuits cost the industry between $7.5 billion and $9 billion per year on average. Plus, another $1 billion to $2 billion in lost sales of new and existing products.