论文

Manufacturing Process Optimization: Simulation-Based Production Line Management under Demand Uncertainty


This article presents a discussion of manufacturing process optimization in the ready-made garment industry through making the management of production lines more effective using AnyLogic software. It shows how simulation of various scenarios can pinpoint effective strategies for maintaining efficiency despite changes in market demand.

Simulated-Based Analysis of Recovery Actions under Vendor-Managed Inventory Amid Black Swan Disruptions in the Semiconductor Industry: a Case Study from Infineon Technologies Ag


Through simulation modeling, this research highlighted the interactions of key system parameters in a disruption phase under different scenarios. A multi-period, multi-echelon serial supply chain was studied with agent-based and discrete-event simulation.

Automatic Component-Based Synthesis of User-Configured Manufacturing Simulation Models


Using simulation models for manufacturing facilities is a common approach for planning, optimizing, and testing different machine configurations and positioning before the actual construction. This paper presented a proof of concept for gradually migrating a master simulation model for shop floor layouts of machines into a product line of different simulation models to explore and find suitable solutions.

Applying a Hybrid Model to Solve the Job-Shop Scheduling Problem with Preventive Maintenance, Sequence-Dependent Setup Times, and Unknown Processing Times


The job-shop scheduling problem was considered with sequence-dependent setup times and preventive maintenance constraints. A hybrid model combining discrete-event simulation and an optimization algorithm in Python was applied to simulate the production process and solve the job-shop problem.

Crane Scheduling at Steel Manufacturing Plant Using Simulation Software and AI


The overhead crane scheduling problem has been of interest to many researchers. While most approaches are optimization-based or use a combination of simulation and optimization, this research suggests a combination of dynamic simulation and reinforcement learning-based AI as a solution.

The goal of this steel plant simulation project was to minimize the crane waiting time at the LD converters by creating a better crane schedule.

The Role of Simulation Optimization in Process Automation for Discrete Manufacturing Excellence


We discuss the application of simulation to estimate a nominal, or target, processing times for work stations on a serial assembly line. The expectation is that having different processing times per station per product will increase the throughput of the line, compared to having a constant time for all stations. A demonstration case at ABB Robotics in Sweden will be presented. This is a small part in the “Process Automation for Discrete Manufacturing Excellence” project (PADME) involving five manufacturing industry partners and four research organizations, that aim at adapting Industrie 4.0 strategies and existing state-of-the-art technologies into new configurations, serving as a framework that can be used by similar industries.

Towards Circular Economy Implementation in Manufacturing Systems Using A Multi-Method Simulation Approach to Link Design and Business Strategy


The recent circular economy movement has raised awareness and interest about untapped environmental and economic potential in the manufacturing industry. One of the crucial aspects in the implementation of circular or closedloop manufacturing approach is the design of circular products. While it is obvious that three post-use strategies, i.e., reuse, remanufacturing, and recycling, are highly relevant to achieve loop closure, it is enormously challenging to choose “the right” strategy (if at all) during the early design stage and especially at the single component level. One reason is that economic and environmental impacts of adapting these strategies are not explicit as they vary depending on the chosen business model and associated supply chains. In this scenario, decision support is essential to motivate adaptation of regenerative design strategies. The main purpose of this paper is to provide reliable decision support at the intersection of multiple lifecycle design and business models in the circular economy context to identify effects on cost.

Simulating Recovery Strategies to Enhance the Resilience of a Semiconductor Supply Network


Enhancing supply chain resilience is of vital importance in today’s business to manage and mitigate the risks, especially in the semiconductor industry challenged with intrinsic long cycle times and short product life-cycles. Transferring production from a primary site to an alternative site after a disaster is one of the strategies to ensure resilience of the supply network. In this study, different types of alternative sites with various levels of preparedness are investigated. A discrete-event simulation is used to evaluate their operational and financial impacts under four different disruption scenarios. The simulation outcomes demonstrate unexpected positive benefits of various alternative sites in terms of fast recovery and resilience building.

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