Question

Case 15.2    Glaser Machine Works

Glaser Machine Works has experienced a significant change in its business operations over the past 50 years. Glaser started business as a machine shop that produced specialty tools and products for the timber and lumber industry. This was a logical fit, given its location in the southern part of the United States. However, over the years, Glaser looked to expand its offerings beyond the lumber and timber industry. Initially, its small size coupled with its rural location made it difficult to attract the attention of large companies that could use its products. All of that began to change as Glaser developed the ability not only to fabricate parts and tools but also to assemble products for customers who needed special components in large quantities. Glaser’s business really took off when first foreign and then domestic automakers began to build automobile plants in the southern United States. Glaser was able to provide quality parts quickly for firms that expected high quality and responsive delivery. Many of Glaser’s customers operated with little inventory and required that suppliers be able to pro- vide shipments with short lead times. As part of its relationship with the automobile industry, Glaser was expected to buy into the lean-manufacturing and quality- improvement initiatives of its customers. Glaser had always prided itself on its quality, but as the number and variety of its products increased, along with ever higher expectations by its customers, Glaser knew that it would have to respond by ensuring its quality and operations were continually improving. Of recent concern was the performance of its manufacturing line 107B. This line produced a component part for a Japanese automobile company. The Japanese firm had initially been pleased with Glaser’s performance, but lately the number of defects was approaching an unacceptable level. Managers of the 107B line knew the line and its workers had been asked to ramp up production to meet increased demand and that some workers were concerned with the amount of overtime being required. There was also concern about the second shift now being run at 107B. Glaser had initially run only one shift, but when demand for its product became so high that there was not sufficient capacity with one shift, additional workers were hired to operate a night shift. Management was wondering if the new shift had been stretched beyond its capabilities. Glaser plant management asked Kristi Johnson, the assistant production supervisor for line 107B, to con- duct an analysis of product defects for the line. Kristi randomly selected several days of output and counted the number of defective parts produced on the 107B line. This information, along with other data, is contained in the file Glaser Machine Works. Kristi promised to have a full report for the management team by the end of the month.

Required Tasks:

1. Identify the primary issue of the case.

2. Identify a statistical model you might use to help analyze the case.

3. Develop a multiple regression model that you can use to help Kristi analyze the product defects for line 107B. Be sure to carefully specify the dependent variable and the independent variables.

4. Discuss how you will model the variables overtime hours, supervisor training, and shift.

5. Run the regression model you developed and interpret the results.

6. Which variables are significant?

7. Provide a short report that describes your analysis and explains in managerial terms the findings of your model. Be sure to explain which variables, if any, are significant explanatory variables. Provide a recommendation to management.

Answer 1

Sol:

The given information is related to the number of defectives occurred in 107B line in Glaser Machine works. Let y be number of defects. X1 be the processing rate. X2 be the overtime hours. X3 be the worker training X4 be the shift. X3 = 1 if worker had taken the training = Yes = 0 if worker had not completed the training = No X4 = 1 = Day = 0 = Night Let y be the dependent variable and X1, X2, X3 and X4 be the independent variables. \r\n (1) The primary issue of the case is number of defectives occurring in the line 107B. \r\n (2) Use multiple regression model to analyse the case. The model is, \r\n y^^= beta_0 + beta_1(X1) + beta_2(X2) + beta_3(X4) \r\n The multiple regression model is, \r\n y^^= beta_0 + beta_1(processing rate) + beta_2(overtime hours) + beta_3(Worker training) + beta_4(shift) \r\n (4) In the model, over time hours(X2)

3: