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Lean Six Sigma
The Lean Six Sigma approach selected to carry out the process improvement initiative enables us to find the root cause of the problem systematically. Our goal is to ensure that the problem we are going to solve should prevent us from repeating the same problem and that the solution at hand should allow us to work towards continuous improvement.
It is common to see the Lean Six Sigma methodology applied in such nonprocess-engineering activities as inventory management, supply-chain optimization, and transportation. Chemical manufacturing companies have adopted Lean Six Sigma in many ways in their process improvement initiatives, especially when dealing with poor yield or wide variation in yield; long cycle times; and process instrumentation/controls performance.1
In a nutshell, the Lean Six Sigma approach embodies both the statistical and process tools to provide for optimization and improvement. It relies heavily on facts (data) and treats data variation as undesirable.
To address a specific process improvement initiative at the Khurais gas train, we used the Lean Six Sigma methodology to improve propane recovery from NGL products. The driving force for such an initiative is primarily the impact of product losses on the hydrocarbon chain throughout the company, especially in NGL products. In addition, operational concerns due to high liquid buildup in the gas export line following the loss of C3 product to the gas export line during the winter months made this initiative critically important.
Lean Six Sigma methodology strictly follows define, measure, analyze, improve, and control (DMAIC) phases. The project starts with problem definition, which breaks down into problem statement, project objective, and project benefits. In Lean Six Sigma methodology, understanding the problems that lead to poor performance requires a specific tool within the define phase. This involves using the supply-input-process-output-customer (SIPOC) table (above) and the process mapping diagram to gain full insight into the problem at hand.
In our case, use of the SIPOC table provides a "birds-eye view" of the process affecting the issue. This is then followed by use of a process mapping tool, a typical process flow diagram to understand in greater detail the movement of C3 in the Khurais gas train. This in turn enables the team to define the problem better.
To quantify the problem, we initiated data gathering on the performance of C3 recovery. Based on data gathering for a given period, a statistical tool—Process Capability Analysis—was used on the poor C3-recovery performance from the NGL products. It was confirmed statistically that for most of the time, the C3 purity in the NGL products does not meet the minimum requirement of 35 vol %. Therefore, the team formulated the project objective to focus on improving the C3 product purity to a minimum target of 35 vol % from the then-current 25 vol %.
Finding the root cause of the problem is the next step. This is achieved by use of the following Lean Six Sigma tools: a "fishbone" diagram, cause-and-effect matrix, and failure mode and effect analysis (FMEA).
The fishbone diagram, which enables the team to explore the causes, is conducted in a brainstorming session among team members. The cause-and-effect matrix prioritizes the causes or identifies which elements contribute most to cause problem. This involves use of rankings on all elements identified as the potential of causing the problem.
Next, the FMEA, used to detail the causes, includes finding the potential failure mode, identifying the impact of this failure on the customer, identifying the potential causes of this failure, and recognizing the current control mechanism to mitigate the failure.
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