Role: Engineering, User Research, Quantitative Analysis
Project Time:: 1 year
Team: Hai V.
Read more about the SureLOC release device on page 23.
The downturn of the oil and gas industry meant that many of Schlumberger's critical suppliers were being shut down. Though field operations were also slowing, certain safety-critical tools were required for every operation and thus continued to have high demand. One of these tools was the electrically controlled release device. The core mechanism inside the device, the bobbin, could no longer be purchased from the original supplier.
In order to keep up with our demand, I was asked to design an efficient and precise way to assemble this technique-sensitive component.
Contextual inquiry: observing experts on the shop floor
As a senior manufacturing engineer with five years of experience with 6 different project teams under my belt, I had seen so often how engineers would come up with fantastic new technology, and the tools needed to assemble and test the technology were an afterthought: they were designed from the comfort of an office rather than alongside the people who would use them. In fact, the tooling many times would be so inadequate that the assemblers would create their own modifications and designs to be able to do their jobs.
For a safety-critical tool, I could not let that happen.
My first step in designing the new assembly system and tooling was contextual inquiry: I observed, asked questions, and listened to the needs of the true experts - needs that often times were ignored due to their lack of a formal education or poor English. To me, these were the people that engineers, including myself, needed to learn from.
Quantifying a qualitative process
Two overarching factors leading to our backlog were inefficiency and technique sensitivity.
There was only one assembler, Hai, that knew how to build this component - a large part of the reason why we had a huge backlog of orders. To understand the current state of the process, I captured a value stream map to identify all of the value-add and non-value add parts of the existing assembly. I measured each step of the current process to calculate the total cycle time (time from work order release to when it is stocked) as well as the total touch time (labor hours spent actually working on the work order). These metrics, when extrapolated to show what delays would be incurred to our field organization, helped me build a case for the funding I would need to continue the project.
I spent the next week taking photos, videos, notes, and understanding every ounce of how and why he could "feel" a good part from a bad one. I tried assembling many parts myself, understanding quickly how easy he made something so complex seem.
Part of the technique-sensitivity issue is that our existing specifications did not capture the assembler's tribal knowledge. To address this, I mapped out our existing specifications and Hai's specifications, quantifying each.
If something felt "too tight," I attributed a maximum torque measurement. If the solder quality "looked bad," I jotted down the solder parameters used.
These parameters, in conjunction with an assessment against IPC-610 solder standards helped me quantify the cause of each resulting failure mode. These metrics helped me capture how I needed to test my new assembly method design to ensure I was achieving better quality.
Brainstorming solutions with Hai, not for Hai
Turns out, Hai already had a ton of brilliant ideas to make his assembly process better. It's just that nobody had captured it. I worked alongside with him to sketch out solutions, building off of each other's ideas based on our own experiences. When we landed on a few final contenders, I created models on Pro-E and 3D printed them so he could try them out. I continued this process, iterating on the design and increasing the fidelity of the prototypes to functional versions with appropriate material choices.
Getting buy-in with quantitative results
To a team engineering professionals, framing the impact of my work could not come from the lens of qualitative design work, though it was an integral part of my process. For legacy designs, a common challenge is getting leadership approval to make changes. Since the original design team is no longer available to speak to the decisions behind critical features, new managers - reasonably so - are often not comfortable signing their names on change orders that are not 100% vetted, even if the potential benefit of the changes could be huge.
To implement my work, I presented quantitative data to assure the leadership team that my design was validated and verified thoroughly, and that making these changes to a legacy design would not be a safety concern.
With the help of our sustaining engineering team, I was able to come up with a case that clearly showed the testing completed at then product's inception and how it compared to my initial testing results and my proposed test plan moving forward. I spoke to the technical risks with the existing design by showing case studies of the failures we had seen in the field and their associated root causes, and how my design had improved on those weaknesses.
My design increased precision by over 79%, reduced assembly cycle time by 77%, and reduced assembly touch time by 57%. This led to an annual saving of $117.k for our product line.
This automated assembly process is currently being used by not only Hai, but his peers as well. This has led to improved floor efficiency, scheduling flexibility, and the ability to ramp up production.
Measuring global impact
A defective split bobbin assembly can result in an unintentional pull-out (UPO) where the wireline cable breaks and the tool string needs to be fished out of the well, an operation that could cost up to $250K per day for a deepwater offshore rig. With the precision improvement found in this project, I aim to reduce the need for this non-value added operation and increase productivity for our field engineers.
Most importantly, measuring personal impact
With the time savings and technique reduction in this project, I was able to free up one full-time bobbin assembler to work on other assets.
I gave Hai the opportunity to develop himself technically and challenge others to learn bobbin assembly – an important factor in boosting morale during the industry downturn.
I believe that introducing automation to our manufacturing environment was a huge step in pushing the bounds of innovation in manufacturing for a traditionally conservative industry. With innovation so focused on the primary source of revenue, new product development, there is minimal disruption to the norm of manual tool assembly. I was excited to be a part of this change, and hope to find more ways to fundamentally alter the way we build, and design to build.