Ship Maintenance Processes with Collaborative Product Life Cycle Management and 3D Terrestrial Laser Scanning Tools: Reducing Costs and Increasing Productivity

Report Number: NPS-AM-11-180

Series: Acquisition Management

Category: Risk Analysis

Report Series: Sponsored Report

Authors: David N. Ford, Thomas J. Housel, Johnathan C. Mun

Title: Ship Maintenance Processes with Collaborative Product Life Cycle Management and 3D Terrestrial Laser Scanning Tools: Reducing Costs and Increasing Productivity

Published: 2011-09-01

Sponsored By: Acquisition Research Program

Status: Published--Unlimited Distribution

Research Type: NPS Faculty

Full Text URL: http://acquisitionresearch.net/files/FY2011/NPS-AM-11-180.pdf

Keywords: Knowledge value added, simulation modeling, portfolio optimization, real options, risk management, technology adoption

Abstract:

The current cost-constrained environment within the federal government and Department of Defense (DoD) requires a cogent approach to cost reductions that will not compromise the productivity of core defense support processes such as ship maintenance, a core process that is central to naval operations. The SHIPMAIN initiative was designed to standardize ship maintenance alternations in order to take advantage of the cost savings from standardizing core processes. A problem in using the SHIPMAIN approach has been that the normal cost-reduction learning curve for common ship alterations, across a series of common ship platforms, has not materialized. This study uses the knowledge value added (KVA) + systems dynamics (SD) + integrated risk management (IRM) methodology to estimate, analyze, and optimize the potential cost savings and productivity improvements available by moving to a ship maintenance approach that incorporates the 3D TLS and collab-PLM tool suite. Results suggest that when the SHIPMAIN process employs 3D terrestrial laser scanning (3D TLS) and collaborative product lifecycle management (collab-PLM) tools, SHIPMAIN will finally obtain the prophesized learning curve benefits. The results indicated that the biggest bang for buck is in using the combination of the two technologies. Results of the KVA and SD scenario analysis provided the financial information required to forecast an optimized portfolio controlling for risk using the IRM methodology and tool suite. Results indicate that both rapid and incremental implementation approaches generate significant savings and that other factors should be incorporated into final implementation of the 3DTLS + collab-PLMtool tools.