Lean six sigma SEP 2025

Description

Lean Six Sigma

Sep 2025 Examination

 

 

Q1. A pharmaceutical company is facing challenges with batch-to-batch variability in its tablet production line, leading to frequent deviations from quality standards. The process improvement team has been tasked with using the DMAIC (Define, Measure, Analyse, Improve, Control) methodology to systematically address the issue. They are considering the use of cause and effect diagrams to identify potential sources of variation, box plots to compare distributions, and control charts to monitor process stability. Given the scenario, how should the process improvement team apply the DMAIC methodology to identify and reduce sources of variation in a pharmaceutical production process using tools such as cause and effect diagrams, box plots, and control charts? (10 Marks)

Ans 1.

Introduction

In the pharmaceutical industry, product consistency and compliance with strict quality standards are paramount. The scenario of batch-to-batch variability in tablet production reflects a significant challenge that could lead to quality defects, regulatory non-compliance, and customer dissatisfaction. To address this, Lean Six Sigma offers a structured approach through the DMAIC methodology—Define, Measure, Analyse, Improve, and Control. This methodology empowers process improvement teams to identify root causes, minimize process variation, and implement sustainable changes. By applying DMAIC in conjunction with quality tools like cause and effect diagrams, box plots, and control charts, the pharmaceutical company can systematically reduce variability and enhance process stability. The following discussion outlines how each phase of DMAIC can be

 

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Q2. A Six Sigma project team is in the analyze phase, tasked with identifying sources of variation in a manufacturing process. They must choose between the chi-square, Student’s t, and F-distributions for hypothesis testing and constructing confidence intervals. The team is debating which distribution best fits their data, which is approximately normal but includes both small and large sample sizes. Their decision will impact the accuracy of their process improvement recommendations. Evaluate the decision to use the chi-square distribution for hypothesis testing in a Six Sigma project’s analyze phase. Critique its suitability compared to the t and F distributions, and justify under what conditions each distribution should be preferred for process improvement decisions. (10 Marks)

Ans 2.

Introduction

In the Analyze phase of a Six Sigma project, selecting the appropriate statistical distribution for hypothesis testing is crucial for identifying and validating sources of variation. The choice among chi-square, Student’s t, and F-distributions depends heavily on the nature of the data, sample size, and the hypothesis being tested. The project team in question is dealing with approximately normal data with both small and large sample sizes. In such a scenario, selecting the right distribution directly impacts

 

 

 

Q3(A). A financial services firm is expanding its product offerings and faces increased operational risks. The process improvement team wants to integrate Failure Modes and Effects Analysis (FMEA) and risk assessment with Six Sigma control charts to identify, monitor, and mitigate process risks, ensuring high service quality. Propose a comprehensive methodology for a financial services firm to use FMEA and risk assessment in conjunction with Six Sigma control charts to proactively manage process risks and improve service quality. (5 Marks)

Q3(A) – Financial Services Firm: FMEA, Risk Assessment & Six Sigma Control Charts

Ans 3a.

Introduction

In the financial services sector, process complexity increases significantly with expansion in product offerings, leading to heightened operational risks. Ensuring consistent service quality while mitigating such risks demands a proactive approach. By integrating Failure Modes and Effects Analysis (FMEA), risk assessment, and Six Sigma control charts, firms can detect vulnerabilities early, measure process stability, and maintain compliance. A comprehensive methodology combining these tools allows the process improvement team to anticipate failures, prioritize mitigation

 

 

Q3(B). A large hospital is facing challenges with inconsistent diagnostic results across different departments and technicians. The management suspects issues with measurement system repeatability and reproducibility (R&R), as well as long-term stability. They want to implement a robust framework to evaluate and enhance their measurement systems, ensuring reliable patient outcomes. Devise a new framework for a hospital to assess and improve the repeatability and reproducibility of its diagnostic measurement systems, ensuring long-term stability and accuracy. What steps would you include and how would you address potential sources of error? (5 Marks)

Ans 3b.

Introduction

In a hospital setting, inconsistent diagnostic results compromise patient safety and trust. When results vary across technicians or departments, it often indicates issues in measurement system repeatability and reproducibility (R&R), as well as long-term stability. A robust framework to evaluate and enhance these systems is essential. By systematically assessing equipment, operators, and environmental factors,