Collecting and prepping manufacturing data can be an arduous task for your team. It’s estimated that for every one hour of data analysis performed, roughly four hours are spent collecting and organizing data.
And then reporting data can also be time-consuming—quality engineers spend roughly 20-30% of their time each week reporting their findings.
In our example today, we will explore a hypothetical use case from a mid-sized consumer electronics manufacturing company that is seeking to save energy to protect the bottom line, analyze energy usage in real time to detect issues, and understand when energy use will be higher at their factory to ensure their infrastructure is sufficient on a seasonal basis.
On-going, Real-time Energy Use Analysis
The team recently deployed Minitab Connect to automate data access and preparation. Minitab Connect provides live analytics when integrated with Minitab Statistical Software. This ensures that charts, analyses, and crucial data are always up to date and easily visible on the Connect dashboard.
Minitab Connect offers a significant advantage over traditional data reporting methods by providing real-time, continuous visibility into your data. The seamless integration with Minitab Statistical Software ensures that your analytics are always up to date, reflecting the most current information. As a result, your team can make informed decisions based on the latest data, which allows for quicker responses to emerging trends and challenges.
In our use case, the team used a smart meter to assess how much energy was being used in kilowatt-hours (kWh) for each piece of machinery. This data was automatically collected and imported to Connect every thirty minutes, saving hours of time that would have been lost to manual collection. Here is the IMR chart for Machine A from the past 24 hours:
As you can see, there are two out-of-spec readings: one at 12:00 PM and another at 7:00 PM. In both cases, the team had set up instant alerts on their Connect dashboard to notify them via text message if the energy readings deviated from the norm for any of the main equipment. Thanks to these alerts, the team was able to promptly investigate and address the issues.
Both out-of-spec readings were caused by overheating. Catching these issues early prevented potential equipment damage and avoided costly repairs.
In the short term, addressing the overheating problems reduced energy waste and ensured efficient equipment operation, which will ultimately lead to lower operational costs.
In the long run, this proactive approach saved time and money by preventing equipment failures and extensive repairs. It also minimized downtime, maintained smooth production, and reduced the need for rework.
See how much time and money Minitab Connect can save your team with our ROI calculator. 
Predict Seasonal Energy Trends
The team used Connect to automatically gather energy use data over 18 months. They wanted to spot trends to predict future energy usage—mostly to ensure they had the necessary infrastructure to handle the volume of energy needed, but also to spot trends to predict budgetary needs and identify areas for energy reduction.
With live analytics, they were able to view their time series analyses on their dashboard. They chose to organize their data by the total energy used by the entire plant each week. Minitab enabled them to gather data expeditiously, generate forecasts for the next six months, and determine whether there was significant seasonality within their data:
The team was able to visualize the clear upward trend, and they noticed that there was a spike in energy use at the plant during the last week of the month, likely to hit production goals. They were also able to determine that they should be prepared for roughly 280,000 kWh per week within the next 6 months—a significant increase from their current readings—unless they could make significant improvements or tweaks.
Due to the real-time smart meter energy readings collected through Connect, the team identified specific equipment and processes that contributed to unusually high energy consumption. For example, they discovered that a particular machine in the production line was using significantly more energy than expected due to outdated components. They upgraded this machine with energy-efficient parts and optimized its operating settings.
Additionally, they adjusted the production schedule to minimize peak energy usage times. By implementing these changes, they not only improved overall energy efficiency but also ensured that production goals were met without exceeding necessary energy thresholds. This targeted approach allowed them to effectively manage energy use and reduce operational costs while maintaining productivity.
Unlock Efficiency and Cost Savings with Minitab Connect and Minitab Statistical Software
Harnessing the power of Minitab’s solutions has transformed the way energy use can be managed. With Connect automating data collection and providing real-time insights, the team could quickly spot and address issues, reducing energy waste and avoiding costly repairs. This immediate feedback loop was crucial for maintaining operational efficiency and controlling costs.
The team not only anticipated future energy demands but also pinpointed areas for improvement. This proactive approach allowed them to make targeted upgrades and adjust production schedules, ensuring they could meet increased energy needs without compromising efficiency.
Minitab’s ecosystem of solutions empowered the team to streamline their operations, save both time and money, and enhance their overall productivity.
