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Development of a useful tool to evaluate quality strategies for the KODAK dope production process

George Hadjigeorgiou- October 1997

 

 

Motivation

Although there are several approaches to quality management, there does not exist a common modeling methodology that reduces these approaches to shop floor terms and allows manufacturing personnel to "simulate" and evaluate different approaches to their day to day quality problems. This project is aimed at beginning to provide a model that can be used to support playing such quality "what-ifs". The development of a specific model could then point out to a more general framework and formulation that can be utilized in estimating a systemís overall quality.

KODAK Dope Production

In order to build such a specific model we focused on a single manufacturing multi-step operation, the KODAK dope production process. This process is a part of the overall film manufacturing since it produces the underlying base of the film. A roll of film can be manufactured in many ways; nevertheless, the basic framework is the same everywhere. The first two parts involve the manufacturing of a sheet that provides the base upon which emulsion and other coatings will be added. In the first part, a base mixture is produced or purchased from outside the company. In the second part, a sheet of this material is formed. The film products we see in the stores are different due to the various coatings that are being added during the production of a particular type of film and the different materials and processes used in the production of different film base sheets.

Figure 1. Film Manufacturing

  Dope Production is essentially a mixing process. Different substances, either solid raw materials or liquid solvents and dyes, enter a continuous maker where they are mixed together producing a very viscous liquid that resembles tapioca in the early stages of the process. The resulting mixture is stored in holding tanks where operators can add quantities of the raw materials in case they determine that more material is needed. The mixture then passes through filters that remove any foreign matter. Immediately after that, the mixture is stored in tanks. The mixture is then further mixed and before entering the roll coating stage portions of the solvents are vaporized in order to produce a more viscous material. Dope Production is monitored by experienced operators who intervene and change parameters of the process.

The quality of dope is critical for the overall quality of the film. It is defined by the relative volatility of the constituents in the actual mixture. It is desired that a uniform product be delivered to the latter stages of film manufacturing. If the concentrations of the chemicals in dope are volatile, the resulting sheet will not have a uniform thickness resulting in poor coatings adhesion and an increase in the number of the defects. Therefore, the overall goal of this project is essentially to evaluate strategies which will keep the concentrations in dope as uniform as possible.

Figure 2. Dope production

 

In order to evaluate such quality strategies, we have built a physical model for the dope production. Since, the dope production is a multi-step process, we have separately modeled the individual steps in the process (machines, operators, controllers). In such a way, the model is more flexible in evaluating different configurations of the process. The model of the process has been compared to actual production data, generating excellent results.

Figure 3. Model of the dope production

 

Figure 4. Comparison of model prediction vs. actual sensor data

 

Applications of the model

  The applicability of the model is very significant since the production managers can utilize it in order to evaluate new scenarios and answer "what-if" questions in their day to day operations. An example of such a what-if question regards the magnitude of a change that an upset in the beginning of the process can generate. By implementing the upset in the model, production managers can find out how much time it will take for such an upset to propagate in the latter stages of the process. Moreover, they can also examine any magnitude changes that were caused by the upset.

 

Figure 5. Evaluation of an upset

 

 Another study that is currently under investigation involves the configuration of the process as a strategy to improve the quality of the product. The implementation, for instance, of a "seriesí vs. a "parallel" configuration could have a significant impact on the quality of dope. The results are inconclusive so far and the study is still under investigation.

 

Figure 6. Series and parallel configurations

 

Figure 7. Series vs. parallel configuration study

 

Other applications of the model include the identification of the most important sources of variability, the optimal (in economic sense) allocation of buffer space in the process as well as the training of the operators.

Additional information

 For additional information, you can view the presentation that George Hadjigeorgiou gave at the 1997 LFM Symposium.

You can also download the original text in pdf or postscript format (for better quality images).

 

 


 This page is written by George Hadjigeorgiou. Last modified on October 6, 1997. It is based on research by Duane S. Boning, Stanley B. Gershwin and George Hadjigeorgiou. It is related to the research efforts of the Leaders for Manufacturing Program at MIT, especially its Research Group 5. Please send comments to ghadjige@mit.edu.

 

Copyright © Massachusetts Institute of Technology 1997. All rights reserved.