Operations management Annotated Bibliography

Course Title: Operations Management

Submission Date: June 24, 2016

Article 1

1. Pistikopoulos, E. N. (1995). Uncertainty in process design and operations. Computers & Chemical Engineering,19, 553-563.

The research paper has reviewed the research conducted in the field of operations process design during uncertainty. The research has focused on identifying the links between different variables that are related to uncertainty and the process optimization problems they may cause. Authors of the article have done in depth literature review and come up with flexibility, controllability and reliability as the main factors that have a direct or indirect relation with causing uncertainty in business operations. Numerical techniques are then discussed to predict and then overcome the negative effects of these variables. Future research trends have been identified to carry out research on uncertainty prediction and use these prediction to improve process optimization.

 

Article 2

2. Mentzer, J. T., DeWitt, W., Keebler, J. S., Min, S., Nix, N. W., Smith, C. D., & Zacharia, Z. G. (2001). Defining supply chain management. Journal of Business logistics, 22(2), 1-25.

According to this research article, there is a greater need to define the term supply chain management today than ever before as more dependency on supplier for goods has risen in the last few decades. Especially international trade has risen exponentially and supply chain management has been applied with different approaches. The definition the research article has come up after a considerable amount of literature review is as follows:

“A set of three or more entities (organizations or individuals) directly involved in the upstream and downstream flows of products, services, finances, and/or information from a source to a customer.”

This definition provides a comprehensive overview of the concept of the supply chain management as a process involving different people and/or different physical location. According to the researchers in the article, the ultimate supply chain management involves different parties like the actual suppliers and actual customers in addition with intermediator suppliers, customers, financial resource and other organizations.

Article 3

3. Fleming, Q. W., & Koppelman, J. M. (2000, January). Earned value project management. Newtown Square, PA: Project Management Institute.

National Security Association (NSIA) has classified “Earned Value” to be a set of 32 criteria that is used to standardize industrial standards. The research produced in the article has considered the topic of earned value from the perspective of a concept that has evolved from PERT or program evaluation and Review Technique. The researchers have evaluated the application of the concept of earned value at different projects. The research suggest that the concept has proven to be effective in managing the operations of an organization but the use of earned value standards is not yet as common as its effectiveness may suggest. The research further suggest than there may be project implementation scenarios where a rise in the project costs may be eminent. Application of earned value to such projects in their advance stages when only 15% of the project is complete can help in predicting such anomalies.

 

Article 4

4. MacGregor, J. F., & Kourti, T. (1995). Statistical process control of multivariate processes. Control Engineering Practice, 3(3), 403-414.

The research in this article is stresses on the importance of statistical process control in general and multivariate process control in specific. The research paper provides an overview of different approaches that are utilized by multivariate statistical processes. The authors of the research paper have studied different methods like Principal Component Analysis (PCA) and Partial Least Squares (PLS) and has shed light on their utilization in continuous and batch multivariate statistical processes. The research suggests that multivariate processes that utilizes the product quality data and process variable data are superior to other statistical process control techniques. The article further discusses practical issues that are encountered when applying the above methods to industrial data.

Article 5

5. Woodall, W. H., & Montgomery, D. C. (1999). Research issues and ideas in statistical process control. Journal of Quality Technology, 31(4), 376.

There is a considerable amount of research that suggests benefits of statistical process control in industrial operations. But the very nature of research in relation to statistical process control mechanisms have some intrinsic issues. This research paper provides details of these issues in depth. Authors have provided an overview of the current research on control charting methods and the issues that are encountered in this kind of research. The authors suggest that variable sample size, sampling interval methods, multivariate methods, and nonparametric methods contribute to the research issues that are encountered when conducting research related to statistical process control in industries. The research further suggests that Schewhart control charts have provided help in process control research but at the same time they leave many unanswered questions. At the end the researchers suggest that statistical process control methods should be applied in changing manufacturing environment to assess their effectiveness.

Article 6

6. Makrymichalos, M., Antony, J., Antony, F., & Kumar, M. (2005). Statistical thinking and its role for industrial engineers and managers in the 21st century. Managerial Auditing Journal, 20(4), 354-363.

The purpose of this research article is to devise a framework for six sigma and statistical thinking in industrial engineering. The paper has also pointed out the key features of how to think statistically. The paper has discussed the advantages of the statistical thinking and provided an overview of the reasons that cause organizations in the modern world “not to think statistically”. The paper has elaborated on the different aspects of six sigma that are utilized while thinking statistically. The findings in the paper suggest a relation between six sigma and statistical thinking. The findings also point to the reasons of why future managers must be capable to think statistically in an industrial setup. One of them is to understand the statistical process control mechanism to improve the manufacturing processes. The paper has focused on practical applications of the findings of the result and hence could prove beneficial in actual industrial engineering.