A data driven estimating procedure for an accurate cost and labor assessment in mold manufacturing

Cost estimation within mold manufacturing is critical for maintaining profitability and competitiveness. This project will look at a data-driven estimating method for accurate cost and labor assessment for quoting of complex molds. We will first analyze the features of molds and manufacturing processes. Next, investigate different methods for cost estimation, such as variant-based (case-based, and parametric), generative (activity-based, feature-based) and hybrid. This procedure will be integrated within manufacturing supply chains, both internal and external processes, such as shipping, steel hardening, and sandblasting, which are outsourced. We plan to develop numerical models to assist in different labor and material cost estimations. These models are expected to be implemented using MS Excel, Visual Basic or other widely available software platforms. Due to pricing of raw materials and outsourcing requirements, dynamic and automated updating will be studied. A data driven integrated method will be developed, which will be tested and compared with practical situations.

Faculty Supervisor:

Guoqing Zhang

Student:

Mohammed Almanaseer

Partner:

Omega Tool Corp

Discipline:

Engineering - mechanical

Sector:

Advanced manufacturing

University:

Program: