Consulting

Applying DOE to Strengthen Manufacturing Reliability

Problem

Our customer, a leading medical device manufacturer specializing in medical and industrial equipment, wanted to improve its sealing process by identifying the factors that most influenced seal strength. The goal was to optimize the process and ensure stronger, more reliable seals.

The organization had previously examined historical process data and attempted an ad hoc approach by adjusting individual process parameters. However, this method did not provide the insights or consistent improvements they were seeking.

Challenges

Two key challenges stood in the way of success:

• The team was unfamiliar with the principles and methods of Design of Experiments (DOE).
• Data was limited due to the significant time required for sample preparation, inspection, and testing.

Solution

After gaining a thorough understanding of the process with our consultants, a DOE approach was recommended, incorporating multiple process parameters simultaneously. The analysis revealed that cure time was the most significant factor affecting seal strength. Using optimization tools, the process was refined to achieve maximum peel strength.

Results

The project delivered measurable impact, increasing seal strength by nearly 20%. The customer was highly satisfied with the outcome and gained a deeper understanding of how to apply DOE methods to optimize future processes.

Applying Advanced Analytics to Support Regulatory Approval

Problem

One of our customers, a manufacturer of medical implants, was working to validate a new sterilization technique. While clinical trials had been completed, the company still needed FDA approval to demonstrate both the efficacy and safety of this new method.

Previous Approaches

The organization initially relied on a function of the coefficient of variation to justify efficacy and safety. However, this approach fell short because the coefficient of variation does not adequately quantify product risk.

Challenges

The project faced several obstacles:

• The samples had already been implanted in animals, so no additional data could be collected.
• The organization did not have staff with the statistical expertise needed to properly analyze the data.

Solution

To address these challenges, ANOVA was used to separate sources of variation within the sample data. A pooled standard deviation of the residuals was then applied in a simulation to establish efficacy and safety limits based on the actual risk of passing defective parts.

Results

With this approach, the customer successfully obtained initial FDA approval and advanced to the next phase, demonstrating that the new sterilization method carried a low risk of producing results outside the established limits during production.

Standardizing Environmental Data Analysis with Custom Macros

Problem

Our customer, a team of hydrologists, needed to analyze environmental data using specialized statistical tests and algorithms that were not built into Minitab.

Challenges

Environmental data is routinely collected and analyzed by hydrologists and environmental scientists, but the industry relies on methods that are often unique to environmental studies. Since these specialized tests were not natively available in Minitab, analysts had to perform the work manually, making the process:

• Difficult and time-consuming
• Error-prone
• Inconsistent across different users

Solution

Minitab experts leveraged Minitab’s macro language to create a library of custom macros that incorporated the specialized methods and tests used in environmental analysis. These macros enabled multiple analysts to apply the same standardized approach, ensuring consistent, reliable results while reducing manual effort.

From Manual Effort to Automated Insights in Film Manufacturing

Problem

Our customer, a specialty film manufacturer, needed to regularly produce capability analyses, graphical summaries, and tolerance intervals for numerous product characteristics across multiple product types.

Challenges

The process of manually generating outputs for every characteristic–product type combination was extremely time-consuming. In addition, analysts had to identify data entry errors and outliers before results could be produced, adding further delays and potential inconsistencies.

Solution

Minitab experts used Minitab Statistical Software’s macro language to develop a custom macro that:

• Automatically flagged data errors and outliers.
• Generated all required analyses for each characteristic–product type combination.
• Delivered consistent, high-quality outputs while significantly reducing analyst workload.

Driving Quality Improvements with Root Cause Analysis

Our customer, an automotive parts supplier, had been struggling with a persistent quality issue for several months. The problem caused significant downtime and large amounts of defective product. Despite repeated attempts, the engineering team had been unable to determine the root cause.

Challenges

The customer needed structured guidance on root cause analysis—specifically, what data to collect, how to analyze it, and how to move beyond trial-and-error approaches. Up until this point, their efforts had relied heavily on educated guesses rather than a systematic methodology.

Solution

One of our consultants worked onsite at the customer’s plant, partnering directly with their engineering team. Together, they walked through the principles of root cause analysis, focusing on how to make the investigation both efficient and effective. The consultant guided the team in identifying the right data to collect and demonstrated the most effective analysis methods for uncovering root causes.

Results

Through this structured approach, the customer discovered a previously unknown measurement system issue that had been masking the true problem. Once corrected, they were able to collect accurate process data and apply advanced analysis tools—including Statistical Process Control, ANOVA, and Multi-Vari charts. These methods revealed the largest source of variation and ultimately uncovered the true root cause of the quality issue.

Building Internal Expertise with Train-the-Trainer Lean Six Sigma

Problem

Our customer, a healthcare organization that provides advanced technologies for medical imaging, laboratories, and point-of-care testing, had recently launched an Operational Excellence (OpEx) program. A seasoned Lean Six Sigma Black Belt within the organization was tasked with taking over team training. However, they did not feel fully equipped to lead this responsibility with the depth of expertise required.

Challenges

The customer needed to develop advanced statistical expertise to ensure their Black Belt could effectively lead the training program. They asked Minitab to provide a train-the-trainer curriculum that would:

• Deepen their understanding of Lean Six Sigma and data analysis.

• Equip them with the skills to confidently train their teams.

• Support the creation of internal training content for Yellow, Green, and Black Belt levels.

   

Solution

The customer’s Lean Six Sigma Black Belt completed a structured training program with Minitab, covering topics from basic statistics to advanced predictive analytics, including theory, concepts, and practical applications. As part of certification, they were required to teach the material back to Minitab, demonstrating mastery.

In addition, the Black Belt partnered with a Minitab Lean Six Sigma Master Black Belt to co-develop the organization’s internal training materials.

Results

After six months of intensive learning, practice, and teach-back sessions:

• The customer’s Black Belt gained the expertise to serve as the internal trainer and statistical analysis leader for the organization.
• Comprehensive internal training materials were developed and finalized.
• The customer now successfully delivers in-house training across Yellow, Green, and Black Belt levels, creating a self-sustaining OpEx program.

Louisiana Department of Health improves emergency evacuation planning

Problem

The Louisiana Department of Health (DOH) plans year-round for large-scale hospital evacuations during hurricanes but faces challenges due to limited hospital surge and ambulance capacity. Air transfers to out-of-state facilities are the only viable option, requiring coordination across multiple agencies. To test and improve their evacuation plans, DOH needed software to simulate patient volumes and timing across various scenarios.

The DOH valuated a range of applications, including Visio-based modeling tools, but Simul8 came out on top because of its combination of value, features, support and the visualization aspect.

Challenges 

Modelling all the eventualities of the evacuation process from patient movement to the airfield, to flights and destinations and aircraft returns. There were a number of process flows to be incorporated with uncertainty.

Solution 

DOH staff were able to easily modify the initial distribution functions and data points as needed, incorporating data from the federal flight contractor on aircraft, flight times, airspeeds, crew requirements and more.

With the simulation's visuals, DOH staff were also able to demonstrate to stakeholders how the entire evacuation process would play out under a range of scenarios, with on screen charts showing the number of patients transferred in the allotted time period.

Results 

Using simulation consultants to simulate the complex evacuation process gave the Department of Health (DOH) immediate insights, showing patient transfers over time and the impact of process changes on total evacuation time. It shifted stakeholders' thinking from relying on fixed numbers to planning for uncertainty and variability, leading to more resilient strategies. Henry Yennie from DOH noted that this mindset shift—and the estimated 60 to 80 hours saved—would have been difficult to achieve with spreadsheets.

Plexus rapidly implements manufacturing process improvements

Problem

With a forecasted increase in demand for a new beverage dispenser, Plexus tasked themselves to develop a simulation model of their current Aftermarket Service department (AMS) to assess and optimize production capacity for an innovative beverage dispenser.

Results

• The simulation results enabled Plexus to provide their client with a 95% confidence interval on the number of units that could be assembled based on current infrastructure constraints.
• As well as showing how many units could realistically be produced, the simulation also provided Ben and his team with valuable recommendations for the optimum level of staffing that would be required to meet this manufacturing commitment.
• Simul8 also quickly saved Plexus over $5,000 by proving that the purchase of additional machinery to add capacity to parts of the assembly process was not necessary.
• Upskilled the team members with the hybrid consulting approach of training the team during the duration of the project. Allowing the Plexus team to put their new skills into practice on a live project 

Practice Makes Perfect: How Perfect Company is Leveraging Simulation to Augment Efficiency in Quick-Service Drive-Through Restaurants

Problem

One of Perfect Company’s QSR customers, operating 500–600 restaurants, faced growing pressure to improve drive-through throughput. Its single-lane design often created bottlenecks, with stalled cars at the front of the queue preventing new orders from being processed. These delays not only frustrated customers but also drove up operational costs. The chain needed a way to maximize drive-through efficiency while maintaining fast, reliable service at the front counter.

Adding to the urgency, the brand wanted to showcase a new operational approach at its annual customer conference—just two weeks after Perfect Company began working with Simul8. To succeed, Perfect Company had to quickly prove its value by delivering a solution that balanced dine-in and drive-through orders and demonstrated how the brand could transform restaurant operations for franchisee partners.

Solution 

Perfect Company partnered with Simul8 to quickly model a digital twin of the restaurant environment. Using brand data, the team tested multiple optimization scenarios, with the simulation accurately reflecting restaurant layouts and prioritizing drive-through orders without disrupting other service channels. The system evaluated and ranked all incoming orders in real time, ensuring throughput gains were balanced across dine-in and drive-through customers.

Simul8’s platform enabled rapid development, with daily check-ins keeping the project on track and delivery achieved in just one week—well ahead of the two-week deadline for the franchise conference. The final model included a prioritization feature that gave restaurant teams clear visibility into order flow and channel performance. Perfect Company also used the simulation to stress-test traffic spikes in a risk-free environment, helping franchise partners understand how operations would respond to sudden surges, such as unexpected walk-in demand. This data-driven approach gave the brand confidence in both performance and scalability.

Results 

The team delivered results the brand could showcase at its annual conference—demonstrating how Perfect Company helps transform operations and drive franchisee success.

By integrating the simulation model into its kitchen software, Perfect Company enabled restaurants to accelerate drive-through service without sacrificing the dine-in experience. This optimization delivered measurable financial impact per hour, helping locations maximize sales while maintaining target service speeds.

Designed as a commercial decision-making tool, the simulation provided clear insights into the profitability of prioritizing drive-through orders. The project equipped the brand with compelling data in time for its annual franchise conference—demonstrating both operational improvements and the strategic value of Perfect Company’s approach.

Automating Data Integration for Smarter Quality Insights

Problem

The company faced difficulties integrating data from multiple plants and disparate sources. Their laboratory data was stored in a LIMS database, while regional site information existed in Excel files. Because the servers were on-premises and inaccessible via the cloud, combining these sources was both time-consuming and complex. They had not previously attempted to solve this problem.

Challenges

During the pilot phase, the team requested a way to export data into SharePoint so that users without access to Connect could still view dashboards. Integrating LIMS data with Excel-based site information was further complicated by the on-premises server setup.

Solution

To address these challenges, a data gateway was installed, enabling secure access to the LIMS environment and allowing data retrieval. Initially, regional site data was transferred using a Minitab-hosted SFTP server, but this was later streamlined with a SharePoint connector. Data was cleaned and monitored using alarms to identify when values fell outside specifications. Dashboards were created featuring IMR and capability charts for hydration testing and coal quality metrics. These dashboards were published via public URLs and embedded in the company’s internal SharePoint, making live data easily accessible across the organization.

Results

The implemented solution established an automated, streamlined data pipeline, eliminating the need for manual data integration and cleanup. Dashboards could now be easily shared through SharePoint, simplifying report distribution. Additionally, alarms were leveraged to monitor SPC table Nelson rule violations, enabling proactive management of product quality.

From Spreadsheets to Seamless Test Visualization

Problem

The customer runs 24-hour tests on their units, often repeating the same test under different configurations. They needed a way to chart and compare these tests side by side to evaluate performance across configurations and units.

Initially, they relied on Microsoft Excel to create individual charts. To compare tests, they copied data between files, which was cumbersome and inefficient—especially when working with more than a few tests.

Challenges

Each test generates about 1,440 records with 150–200 columns of data. Beyond the raw test data, each file contains 14 tabs of additional information. Managing and visualizing this volume and structure of data in Excel made comparisons difficult and time-consuming.

Solution

With Minitab Connect, the test data is ingested into a centralized database table. This consolidation enables charts to be configured across all tests, simplifying comparisons and eliminating manual data manipulation.

Results

By leveraging Minitab Connect’s tables, charts, dashboards, and slicers, the customer can now:

• Compare multiple tests on the same unit.
• Compare the same test across different units.
• Identify which configurations and unit builds deliver the best results.

From Raw JSON to Real-Time Dashboards: Accelerating Product Insights

Problem

The customer launched a new product line and needed to access and analyze the large volumes of data generated for each unit. Much of this data was stored in JSON format, which was difficult to work with directly. To ensure a successful launch, they wanted a way to transform this raw data into a relational format, enabling them to identify potential issues before they became problems.

Challenges

Deployment presented several obstacles:

• The core deployment team was not located at the manufacturing site, making communication and collaboration more complex.
• Because the product was new, the team faced “growing pains” in understanding the process and determining the exact data required.
• The data itself was massive and complex. Each test contained over 50,000 lines of JSON data, requiring custom code to extract and restructure into a relational format for analysis.

Solution

With Minitab Connect, the team implemented a Progress Data Gateway to collect multiple test results for each unit produced. Connect was then used to process the large JSON objects and restructure them into relational tables, making the data more accessible and ready for analysis.

Results

By leveraging Minitab Connect’s tables, charts, dashboards, and slicers, the customer can now:

• Visualize multiple test results for a single unit.
• Compare the same test across different units.
• Gain insights into which configurations and unit builds are most successful.

This streamlined approach not only enabled the customer to analyze their new product line effectively but also helped them proactively address potential quality issues during launch.

Boosting Conversions by Enhancing Cart Visibility

Problem

Our customer was experiencing low conversion rates in their buy flow.

Challenges

The buy flow lacked visibility into cart details, leaving customers uncertain about what items they had in their cart at different stages of the process. This lack of clarity contributed to drop-offs and reduced conversions.

Solution

Minitab consultants designed an experimental campaign that dynamically pulled cart details from the data layer and displayed them clearly at each step of the buy flow. This gave customers a consistent view of their selections throughout the process.

Results

The experiment led to a significant reduction in bounce rate and delivered a measurable increase in overall conversions, improving the customer’s revenue performance and user experience.