Date of Graduation


Document Type


Degree Type



Statler College of Engineering and Mineral Resources


Industrial and Managements Systems Engineering

Committee Chair

Bhaskaran Gopalakrishnan

Committee Co-Chair

Kenneth R. Currie

Committee Member

Thorsten Wuest

Committee Member

Todd R. Hamrick

Committee Member

Konstantinos A. Sierros


This dissertation investigates the minimization of part design with self-locating features. The research focuses primarily on self-fastening characteristics, standardization of parts, and minimal use of fasteners. Further, the present research studies the design for base parts in the construction of a moving joint system, in order to locate potential part and system design improvements. This process may then be extended to industrial applications in the manufacturing industry. Relatively little work to date has examined the significance of Design for Manufacturing Techniques (DFMT), with their inherent machine element systems and machining parameters to investigate which DFMT has the most influence on cost reduction and increasing throughput, and under which circumstances. As such, this dissertation analyzes the inter-operational and synergistic elements of the DFMT, machine element systems, and machining parameters. The parametric specifications for the DFMT are examined and integrated with the cost and productivity-related information. In sum, this research applies DFMT to product design.

The trade-off between cost of manufacturing and productivity in terms of DFM alternatives was subject to preliminary model development and sensitivity analysis. For each DFMT and associated machine element systems and Machining parameters, process planning was used effectively with computer-aided tools to enhance the evaluation impact of the dialogue between the design and manufacturing functions. Expert systems and systematic algorithms are inherently incorporated into the software tools used herein. Generative process planning software is used to measure and analyze sensitivity in plan effectiveness, particularly where material property attributes are changed. The shift that occurs according to process plan attributes is explored. These attributes are presented by manufacturing cost and production rate with respect to variations in specific material properties. The research analyzes four DFMT:

  1. Modifying the selection of raw material
  2. Modifying quality
  3. Modifying geometry
  4. Modifying the selection of process/es

In terms of organizing and evaluating the work, a systematic algorithm was developed, discussed, and tested in this dissertation. This algorithm has sequenced elements to investigate and analyze each DFMT. This analysis identifies several potential process plans, from which the plan with the lowest projected cost and highest production rate is selected and constructed. The developed process plans illustrate the importance of alternative DFMT, without impacting product functionality. Each process plan attempts to decrease production cost, maintain quality, and increase throughput. The results of these plans show their respective effectiveness in relation to part utilization, process, and system-level parameters (such as surface finish, tolerance, heat treated condition of the material, geometry, material hardness, melting point, production quantity, cutting tools, cutting fluids, cutting conditions, and machine tools). The criteria for effectiveness include machining cost, tool cost, and throughput.

From this data, the current study determines the most appropriate DFMT and examines underlying alternate machine element systems and machining parameters for each process plan. The effects of DFMT and inherent use of varying machine element systems and machining parameters on cost and productivity-based objectives are also examined. This enables exploration of the selected DFMT choice, according to effective cost reduction and production rate improvement for varying product design. The modified process plan is then compared to the original process plan to highlight areas of improvement. In this comparison, the results of DFMT analysis show significant influence on cost reduction and production rates. These findings suggest that further beneficial outcomes and variety might be obtained by applying this algorithm.