论文

This work simulated some alternatives of dynamic allocation of additional human resources in a company that produces various products from Pupunha palm. Its goal was to increase the average amount of trays produced per day in this line through a hybrid application of discrete event and agent-based simulation. Two different decision-making forms were proposed to find out which workstation should have received an additional operator. The first proposal was made on the level of occupancy of the operators, while the second one was made on the queue size. The computational model was operationally validated by comparing its results with the actual production data of the company.

Symbiotic simulation is a paradigm that emphasizes a close association between a simulation system and a physical system, which is usually beneficial to at least one of them and not necessarily detrimental to the others. Aimed at extending previous work in symbiotic simulation, this paper proposes a framework of symbiotic simulation that can be used to improve the performance of a production system controlled by an enterprise system.

Dynamic models are used to describe the spatio-temporal evolution of complex systems. It is frequently difficult to construct a useful model, especially for emerging situations such as the 2003 SARS outbreak.Here we describe the application of a modern predictor-corrector method – particle filtering – that could enable relatively quick model construction and support on-the-fly correction as empirical data arrives.

The labor-intensive nature of construction projects requires proper management and efficient utilization of labor resources. Improvement of labor productivity can enhance project performance and thereby lead to substantial time and cost savings. Several studies focused on identifying the effect of different factors on labor productivity, whereby the learning curve factor proved of paramount importance. Although previous research efforts developed models to represent the learning curve effect using traditional simulation approaches such as System Dynamics (SD) and Discrete Event Simulation (DES), none of these studies used Agent-Based Modeling (ABM) techniques. This study takes the initial steps and presents work targeted at analyzing the effect of learning on labor productivity using ABM.

In order to cope with the frequent unpredictable changes that may occur in manufacturing systems, and to optimize given performance criteria, the assignment of workers can be decided online in a dynamic manner, whenever the worker is released. Several studies, in the ergonomics literature, have shown that individuals' performances decrease because of their fatigue in work. In manufacturing context, the workers’ fatigue impacts the task durations. Therefore, we propose to solve the online workers assignment problem through a heuristic, which takes this workers' fatigue into consideration, so as to minimize the mean flowtime of jobs.

This research proposes and tests an integrated framework for bottom-up simulation of performance in construction projects. The proposed framework conceptualizes construction projects as systems-of-systems in which the abstraction and micro-simulation of dynamic behaviors are investigated at the base-level consisting of the following elements: human agents, information, and resources.

Projects in mechanized tunneling frequently do not reach their targeted production performance. Reasons are often related to an undersized or disturbed supply-chain management of the surface jobsite. Due to the sensitive interaction of production and logistic processes, planning and analyzing the supply-chain is a challenging task.

Workers cross-trained with multiple tasks can improve the workforce flexibility for the plant to handle variations in workload. Therefore, it is necessary to study the dynamic multi-skilled workforce planning problem of production line with the application of cross-training method.

Looking for new improvement options such as new dispatching rules of an existing semiconductor fabrication facility, a detailed model is indispensable to check the data quality as well as detecting main influences of the facility and finally testing the new optimization approaches.

Utilising dynamic simulation methods to estimate manufacturing resources, can improve unit cost estimation and aid design decisions. This paper introduces a framework specification that combines Computer Aided Design (CAD), Computer Aided Process Planning (CAPP) and Discrete Event Simulation (DES) technologies.