The development of the two-step optimization approach, as seen in Part 1 of the paper, can then be extended to a total water system. The total water system comprises two subsystems: namely, water-using units and wastewater treatment system. In this paper, the proposed approach utilizes mixed integer linear programming (MILP) and nonlinear programming (NLP) in the two-step optimization approach to generate multiple optimum solutions, called "class of good solutions", for the total water system design problem. A case study from the literature is used to illustrate the proposed approach, and comparisons with the results from the current techniques were then made to demonstrate the proposed method's strength.
The intent of this paper is to share the Root Cause Analysis (RCA) that is addressing the small-scale project performance issues, focusing on project schedule and milestone deliverable completion delays. Moreover, investigative data analysis was performed for similar previously completed industrial projects, revealing delay causes and different aspects of project performance issues, including scope creep, quality, stakeholder's management and communication gaps. Finally, the corrective action plan is put in place to ensure continuous project performance improvement, by closing all gaps throughout project life cycle phases. The methodology developed in this paper takes into consideration the various types and nature of small industrial projects with budget ranges from $20,000 to $4,000,000, and a two-year execution time frame. The methodology involved data gathering from 36 previously completed projects, as well as interviews with key stakeholders. Moreover, it included Ishikawa "Fishbone" diagram and a gap analysis model to deep dive into the root causes and gap analysis. Finally, a road map addressing the required recommendations was formulated to ensure excellence in project management execution.
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