Process for reducing preliminary engineering costs for multi-sided steel poles

Abstract

Preliminary engineering for fabrication of multi-sided steel poles encompasses two efforts: planning to allocate available human and technical resources, and engineering design to deliver the most cost effective proposal. Steel pole companies strive to manage these efforts effectively, seeking to maximize the utilization of the available resources and workforce productivity. Managers need to be able to reduce costs associated with the preliminary design because there is no financial reward unless the company receives a contract for fabrication. The results reported here will enable engineers and managers to direct the resources where they are needed most and maximize productivity and efficiency. In the current state of practice, the entire pole must be designed in order to provide an accurate estimate of pole weight which is the primary driver of pole cost. This process usually takes in excess of an hour per pole. By streamlining this preliminary design process, engineers and managers are able to focus their time on more profitable efforts.

The objective of this research is to reduce the amount of time spent in preliminary pole design. The methodology is based on developing predictive models using regression techniques that estimate pole weight as a function of several key parameters including pole height, "x-force", "y-force", "z-force", ice thickness, and wind speed. Design data were collected for over 300 multisided steel poles used in the electrical transmission industry in the United States. Results indicate that the predictive models account for approximately 87% of the variability in pole weight thus showing promise as a surrogate for the more time consuming current preliminary design process. In order to assess the time-saving effectiveness of the predictive models, value stream mapping was used to characterize the current preliminary pole design process versus the preliminary pole design process based on the predictive models. The purpose of value stream mapping is to determine pole design productivity, both before and after the predictive models are employed. The value stream map showed that utilizing the developed models would reduce the duration of the design and estimating process by approximately 20%. The validation process of the developed models showed that the models can provide consistency as well as accuracy that are better than the traditional process.