Build Better Batteries with Analytical Tools
people think of building things, they think about tools. While
hammers, screw drivers, wrenches and machinery are critical to building
things, analytical tools are just as important. Without the appropriate
problem solving "gear," you may end up building something that breaks,
doesn't last long, takes a long time to produce or costs more than
anticipated. Naturally, the more complex the item or component, the
greater the need for analytical "instruments."
Batteries are Literally Power Packed… So A Lot Goes Into Making Them
The process of designing, creating and
manufacturing batteries is complex due to various factors. A key
challenge in this process is managing the intricate chemistry involved,
as battery performance is driven by chemical reactions.
Batteries are made up of different materials, each with unique properties that can impact a battery's conductivity, stability and durability. Maintaining strict control and precision throughout the manufacturing process is crucial to ensure quality and performance testing is robust. This is particularly important for safety-critical applications, such as electric vehicles. The mind map below, produced in Minitab Workspace demonstrates some more specifics around these complexities:
Analytical Problem Solving "Tools" Can Help Address These Complexities
Utilize Brainstorming and Project Management Templates to Define the Problem, the Project and the Desired Outcome
Defining your project with a project charter and brainstorming the contributing items to both the product and the manufacturing process is critical to tackling the challenge itself. Maybe you're not starting from scratch and you need to use other tools like a Fishbone Diagram or C&E Matrix to identify causes of poor performance. Regardless, when tackling complex products and processes, proven templates allow you to outline the expected outcome, measure and replicate success.
Use Analytics to Design the Optimal Combination of Chemicals and Materials to Maximize Performance
Once you define your objective (e.g. capacity, voltage or cycle life) and understand your key factors, design an experiment to optimize the combination of variables that impact battery performance or the manufacturing process. You can run the full experiment, run a screening design or even use predictive analytics to help you identify the most impactful factors.
Use Reliability Tools to Estimate the Probability of Failure and Identify Ways to Improve Battery Durability
Once you design the battery for ideal performance, you want to make sure it lasts. Using Accelerated Life Testing, manufacturers can simulate years of use in a short period and assess the reliability of the battery. Then using a Failure Modes Effects & Analysis (FMEA), identify potential failure modes and implement corrective actions to mitigate risk of failure.
Monitor Quality of Product and Process Using Quality Tools
Whether you're manufacturing your first batch of batteries, ramping up production or you're already in high volume production, maintaining and improving quality is everyone's job. Whether you're using more traditional solutions like Measurement System Analysis or Statistical Process Control or more emerging techniques like machine learning, you can reduce costs and waste while improving the performance of your products by having a robust quality analytics framework.
The original blog is written by Joshua Zable for Minitab.