Robust Line Planning in Case of Multiple Pools and Disruptions

Assembly process sheets are formal documents used extensively within automotive original equipment manufacturers (OEMs) to document and communicate assembly procedure, required tooling, contingency plans, and time study results. These sheets are authored throughout the vehicle life-cycle. Further, various customers use these sheets for training, analyzing the process, and line-balancing. In this research, the primary focus is the time studies analysis that is completed using knowledge contained within the assembly process sheets. In this research, a method and software tool are developed to utilize coupling between part descriptions and process descriptions for assembly time studies. The method is realized through the development of a standardized vocabulary for describing work instructions, a mapping from work instructions to MTM codes, and a tool for extracting relevant part information from CAD models. The approach enables process planners to establish part-process coupling, author work instructions using the controlled vocabulary, to estimate assembly time. A prototype system is developed and tested using examples from an automotive OEM.

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Integrating Line Planning, Timetabling, Passenger Routing and Vehicle Scheduling

Integrated Optimization in Public Transport Planning - Springer Optimization and Its Applications ◽

10.1007/978-3-030-46270-3_5 ◽

2020 ◽

pp. 99-116

Author(s):

Philine Schiewe

Keyword(s):

Vehicle Scheduling ◽

Line Planning ◽

Passenger Routing

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Simulation application of three-dimensional GIS based on full-scenario intelligence in power grid company transmission line planning

Journal of Physics Conference Series ◽

10.1088/1742-6596/2083/3/032023 ◽

2021 ◽

Vol 2083 (3) ◽

pp. 032023

Author(s):

Le Zhang

Keyword(s):

Data Collection ◽

Power Grid ◽

Three Dimensional ◽

Line Planning ◽

Mobile Gis ◽

Time Performance ◽

Gis Data ◽

Power Grid Planning ◽

The Cost ◽

Grid Planning

Abstract Traditional data collection and review methods in power grid planning have always had the problems of time-consuming, poor real-time performance, and cumbersome processes. The application of mobile GIS solves the problems of data collection and review methods and makes more efficient use of mobile GIS terminal collection. The data of the mobile GIS solve the urgent problems that need to be solved since the popularization and application of mobile GIS. This system implements functions such as storage, transmission, and review based on mobile GIS data, which will greatly improve the efficiency of data collection by mobile terminals and reduce the cost of data collection. Realize the planning simulation of the power grid under the intelligent cycle of the whole scene.

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A Modified Artificial Bee Colony for the Non-Smooth Dynamic Economic/Environmental Dispatch

Engineering, Technology & Applied Science Research ◽

10.48084/etasr.2098 ◽

2018 ◽

Vol 8 (5) ◽

pp. 3321-3328 ◽

Cited By ~ 3

Author(s):

Ι. Marouani ◽

A. Boudjemline ◽

T. Guesmi ◽

H. H. Abdallah

Keyword(s):

Artificial Bee Colony ◽

Random Search ◽

Line Planning ◽

Bee Colony ◽

Search Mechanism ◽

Loading Effects ◽

On Line ◽

Explosion Method ◽

Metaheuristic Techniques ◽

Emission Dispatch

This paper presents an improved artificial bee colony (ABC) technique for solving the dynamic economic emission dispatch (DEED) problem. Ramp rate limits, valve-point loading effects and prohibited operating zones (POZs) have been considered. The proposed technique integrates the grenade explosion method and Cauchy operator in the original ABC algorithm, to avoid random search mechanism. However, the DEED is a multi-objective optimization problem with two conflicting criteria which need to be minimized simultaneously. Thus, it is recommended to provide the best solution for the decision-makers. Shannon’s entropy-based method is used for the first time within the context of the on-line planning of generator outputs to extract the best compromise solution among the Pareto set. The robustness of the proposed technique is verified on six-unit and ten-unit system tests. Results proved that the proposed algorithm gives better optimum solutions in comparison with more than ten metaheuristic techniques.

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