Date of Award

May 2020

Document Type


Degree Name

Master of Science (MS)


Mechanical Engineering

Committee Member

Joshua D Summers

Committee Member

Mary E Kurz

Committee Member

Gregory M Mocko


The objective of this thesis is to identify change management processes in manufacturing and, if they exist, identify challenges and opportunities for improvement. There are many changes encountered in manufacturing as the advances of automation are integrated within production. For this reason, a change management process is required to effectively and efficiently implement these changes.

To research this, a case study was conducted at a large manufacturing firm (more than ten-thousand employees). The facility studied produces low volume (~one per week), high complexity (~million components) products. The case study spanned six months, in which sixteen interviews were conducted with nine people from three different functional groups. The case study focused on a change to production, which was an automated machine that was implemented in the facility. This was not a change to the product, but a newly configured production station resulting in a decrease in automation level (bringing more manual activity into the task). The previous manufacturing method was fully automated but was not robust. Therefore, the change was to increase the human-robot cooperation in the robotic system. This study investigated the change process for this newly implemented automation.

This was identified as a good case example to study due to several reasons. First, this was implemented within the past five years, which meant that people involved in the change process were still present. In addition to this, since the machine was still in operation it meant the propagation effects were stable and the changes were kept. Another reason this was a good example, was because this was a large-scale investment (~million dollars). This meant the return on investment (ROI) was high, leading to more attention to detail and higher resource allocation. From a research perspective, these reasons ensure the process was a critical case for study.

Many change management processes align with the following high-level process: identify opportunity, gather approval to find a solution, form teams to solve, discover a solution, review, deploy a solution, and measure the solution. The change management process identified through the interviews followed this general pattern. In this model, thirty-four tasks were identified. Through a series of follow-up interviews, the process model was validated. However, obstacles were identified throughout some of the tasks in the process that encountered many changes. To explore this, a collaborative design resistance model was applied to see whether the model could accurately identify the tasks of highest resistance. The resistances were applied to the objective data from the interviews, such as team size and communication, and then compared to the subjective obstacles. From this, it was determined that the resistance model accurately predicted the challenges throughout the process.

This research resulted in a mapped change management process for typical automation implementations. It additionally helped discover opportunities for making these implementations more efficient by mitigating the resistances. Motivated from this study, the following are some opportunities that were discovered for future work: conducting workshops to have participants build the change process model, studying the process at a small-medium enterprise, studying the process at a company with product change (high volume, low complexity).



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