The current work used discrete event simulation techniques to model the economics of quality within an actual automotive stamping plant. Automotive stamping is a complex, capital intensive process requiring part-specific tooling and specialised machinery. Quality control and quality improvement is difficult in the stamping environment due to the general lack of process understanding and the large number to interacting variables. These factors have prevented the widespread use of statistical process control. In this work, a model of the quality control techniques used at the Ford Geelong Stamping plant is developed and indirectly validated against results from production. To date, most discrete event models are of systems where the quality control process is clearly defined by the rules of statistical process control. However, the quality control technique used within the stamping plant is for the operator to perform a 100% visual inspection while unloading the finished panels. In the developed model, control is enacted after a cumulative count of defective items is observed, thereby approximating the operator who allows a number of defective panels to accumulate before resetting the line. Analysis of this model found that the cost sensitivity to inspection error is dependent upon the level of control and that the level of control determines line utilisation. Additional analysis of this model demonstrated that additional inspection processes would lead to more stable cost structures but these structures many not necessarily be lower cost. The model was subsequently applied to investigate the economics of quality improvement. The quality problem of panel blemishes, induced by slivers (small metal fragments), was chosen as a case stuffy. Errors of 20-30% were observed during direct validation of the cost model and it was concluded that the use of discrete event simulation models for applications requiring high accuracy would not be possible unless the production system was of low complexity. However, the model could be used to evaluate the sensitivity of input factors and investigating the effects of a number of potential improvement opportunities. Therefore, the research concluded that it is possible to use discrete event simulation to determine the quality economics of an actual stamping plant. However, limitations imposed by inability of the model to consider a number of external factors, such as continuous improvement, operator working conditions or wear and the lack of reliable quality data, result in low cost accuracy. Despite this, it still can be demonstrated that discrete event simulation has significant benefits over the alternate modelling methods.

Thesis (Ph. D.)--Ohio State University, 2007. / Title from first page of PDF file. Includes bibliographical references (p. 265-278).

Thesis (Ph. D.)--Ohio State University, 2008. / Title from first page of PDF file. Includes bibliographical references (p. 152-158).

In stamping operations, sheet metal is formed into a desired shape by pressing it in a hydraulic or mechanical press between suitably shaped dies. As a predominant manufacturing process, sheet metal forming has been widely used for the production of automobiles, aircraft, home appliances, beverage cans and many other industrial and commercial products. A major effort till date on stamping processes monitoring has been focused on investigating variations in the press force. Given that the press force itself is an integral of the contact pressure distribution over the die and binder contact interfaces, it is conceivable that defects may be better identified by analyzing the contact pressure distribution directly at the tooling-workpiece interface, instead of measuring the press force, which is less reflective of the localized forming process due to its nature as a secondary effect. It is thus desirable that a new, integrated sensing method capable of directly assimilating forming pressure distribution in the tooling structure be devised for improved stamping process monitoring. Designing such a distributed sensing scheme and analyzing the feasibility of its structural integration into a stamping tooling structure is the objective of this reported work. In this context, four research tasks have been identified and examined during the course of this work: 1) Devising a New, Embedded Sensing Method The new sensing method monitors stamping processes by means of an array of force sensors structurally integrated into the stamping tooling. The ability to directly measure local forming events by means of such an integrated and distributed sensing provides a new means of performing defect detection and process monitoring. Such a distributed sensing system overcomes the limitations of traditional tonnage and acceleration sensing systems which are focused on the measurement of indirect, global parameters. The new method is based on the evaluation of spatially continuous pressure surfaces from spatially discrete sensor measurements that are directly related to the local events at the stamping interface. To evaluate the effectiveness of this method, a panel stamping test bed equipped with an array of embedded force sensors has been designed, modeled and fabricated. Data obtained from experiments conducted on the test bed indicates that the new sensing method can be highly effective in process monitoring of stamping operations. 2) Reconstruction of Spatio-Temporal Distribution of Contact Pressure Structurally integrating sensors under tooling surfaces reduces the surface rigidity of the tool, thus limiting the number of sensors and the locations at which they can be embedded. This in turn affects the reconstruction of contact pressure distribution on the tooling surface. Numeric surface generation methods, such as Bezier surfaces and Thin Plate Spline surfaces offer a method for estimating the contact pressure distributions on the tooling surfaces from a sparse distribution of sensors. The concept of interpolating force distributions using surfaces has been investigated by researchers previously. However, selection of the surface generation method has remained largely an ad hoc process. The work presented here addresses this issue by using tooling interface contact pressure distribution information obtained from FE simulations as the basis for evaluating the accuracy of two commonly employed surface methods mentioned above. In order to reach a generic conclusion, the mathematical background of these schemes has been examined in light of the purpose at hand. The results indicate that an interpolative scheme such as the Thin Plate Spline surfaces (TPS), which can estimate the contact pressure distributions more accurately in a multi-sensor environment. The local and global accuracies of the Thin Plate Spline surface modeling technique have been experimentally evaluated using a sensor embedded stamping test bed designed for the purpose. 3) Modeling of Contact Pressure Distribution at the Sheet Metal-Tooling Interface Information about the contact pressure distribution at the tooling interface is critical to identifying the accuracy of numeric schemes that estimate by interpolation or approximation the contact pressure at any point on the tooling surface, based on a limited number of spatially distributed sensors. Furthermore, such knowledge is valuable in identifying operational parameters for the sensors to be integrated into the stamping tooling structure. In the absence of a tractable analytic method of determining the contact pressure distribution on stamping tooling surfaces, Finite Element models of a stamping operation have been created. Furthermore the drilling of sensor cavities under the working surfaces of the dies adversely affects the working life of stamping dies and their strength. The accuracy of analytic fatigue failure mechanics in evaluating the effect of parameters, such as embedding depth and sensor rigidity, on the operational life of the die, suffers from uncertainty in the estimation of stress concentrations around sharp geometric features of the sensor cavity. This shortcoming has been circumvented by the creation of FE models of the sensor cavity for more accurate estimation of stress concentrations around sharp geometries. The effect of different embedding materials on the sensitivity of embedded sensors has also been evaluated based on these models. 4) Defect Detection in Stamping Operation The ultimate goal of this thesis research was to study the feasibility of identifying defects in a stamping process based on the contact pressure distribution surfaces. This was achieved in this reported work by spatio-temporal decomposition of ‘parameters’ derived from the contact pressure distribution surfaces. Here ‘parameters’ refers to quantities such as the minimum, maximum, and mean contact pressures. These parameters have a time-varying spatial location as well as magnitude value associated with them. The feasibility of defect detection in stamping operations based on such parameters has been investigated. In addition to these focal areas, the design and implementation of a stamping test bed equipped for distributed contact pressure sensing has also been researched. This test bed was utilized for experimental verification of the developed theories and numerical models. Design of the proposed test bed required research into additional topics like the design of a protective package for embedded sensors and the effect of sensor embedding depth on contact pressure measurements. These issues have been addressed in this work, culminating in the experimental demonstration of the embedded pressure sensing system for process monitoring in the sheet metal stamping processes.

<p> Tool life during the precision stamping of stainless steel sheet (AISI 301) has been studied with particular emphasis on reduction in the punch diameter and part hole size due to tool wear. Two analytical models for predicting tool life in terms of number of quality parts that could be stamped between two re-grindings have been proposed using a combination of Archard's wear model and punching force. The proposed tool life models have been verified by experiment trials with a round M2 punch and die. The trials were carried out on a precision progressive die in an industrial environment.</p> <p> The first tool life model calculates the pierced hole diameter variation for a given tool from sheet material properties and gives an estimation of number of parts that could be stamped for a given tolerance on a hole size. The second tool life model calculates number of parts with respect to the allowed burr height. Both of the proposed models are derived using sheet material properties such as sheet thickness, strength coefficient (K), strain hardening index (n) and material elongation (A); process parameters such as die clearance and friction coefficient; punch characteristics such as normalized wear rate, punch diameter and punch edge radius. Finite element analysis was also employed to simulate the hole piercing process to predict burr height. The results from the proposed tool life models, FE modeling and the experiments are in good agreement.</p> / Thesis / Master of Applied Science (MASc)