Academic articles

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.

Generic Semiconductor Manufacturing Simulation Model

Simulation is one of the most used approaches to analyze semiconductor manufacturing systems. However, most simulation models are designed for single-use applications and study a limited set of problems that are not reusable afterwards. This paper proposes a generic, data-driven simulation model to evaluate and analyze a wide range of problems arising in modern semiconductor manufacturing systems.

Applying Simheuristics for Safety Stock and Planned Lead Time Optimization in a Rolling Horizon MRP System under Uncertainty

Material requirements planning (MRP) is one of the main production planning approaches implemented in enterprise resource planning systems, and one that is broadly applied in practice. In this paper, a multi-stage and multi-item production system is simulated by considering random customers’ demands and other sources of uncertainty.

Simulating Backfill Operations for Underground Mining

This article focuses on the simulation model that was developed for Sibanye-Stillwater’s underground platinum mining operations in Nye, MT. The model was designed to help the mining company understand how bottlenecks move through their operations, to help identify which resources are constraining underground mining production increases, and to understand where capital investments are needed in backfill operations.

Using Simulation to Analyze the Predictive Maintenance Technique and its Optimization Potential

The Predictive Maintenance technique offers a possibility to improve productivity in semiconductor manufacturing. Current research on Predictive Maintenance mainly focuses on its technical implementation. By applying discrete-event simulation, the research team provide results on how maintenance strategies can help optimize machine operations, and how the technique contributes to an overall improvement of productivity in wafer fabrication.

Building a Predictive Analytics Simulation Model of a Semiconductor Manufacturing Facility

The purpose of the article is to create a predictive analytics simulation model to help managers anticipate manufacturing issues. It integrates specifically the involvement of human resources in the manufacturing systems. The predictive analytics simulation model also includes the main existing interactions between the operators and the manufacturing system.

Simulation-Based Scheduling and Planning Approach to Job-Shop Production System

This paper proposes a simulation-based decentralized planning and scheduling approach to improve the performances of a job-shop production system, compliant with a semi-heterarchical Industry 4.0 architecture. To this extent, to face the increasing complexity of such a scenario, a parametric simulation model able to represent a wide number of job-shop systems is introduced.