When it’s your business to provide the machines that local and multinational manufacturing companies rely on to make their products, ensuring the accuracy of those machines is crucial – not just for your customer, but for their customers, too.
That was the challenge faced by i-Stone Technology in Malaysia, a one-stop source for engineering solutions including the design and fabrication of test equipment, software development, production of jigs and fixtures, and electronics engineering. When some customers raised questions about accuracy, i-Stone set out to find a solution that would give both their own inspectors and their customers complete confidence that the test equipment i-Stone provides performs to specifications.
Functional tester developed by i-Stone
i-Stone customises a wide range of equipment to fit each customer’s specific needs. Though their success prompted rapid growth from just a handful of employees in 2007 to nearly 100 employees today, i-Stone still found it challenging to measure and quantify the consistency of their test equipment before passing this equipment on to their customers.
The equipment was evaluated based on customer specifications only, leading to discrepancies and variation in the results found by i-Stone’s inspectors and those obtained by customers. This resulted in additional costs to fix the problems, not to mention the unmeasurable price of customer dissatisfaction.
How Minitab Helped
“We were introduced to Minitab Statistical Software by one of our customers, so using samples provided by existing customers and running the Gage R&R analysis in Minitab, we began to think about demonstrating the consistency of the equipment before it was dispatched,” said Project Manager Lee Yong Ho.
Lee entrusted one of his project engineers, Noorsalzatul Azura, with the task of using the Gage R&R tools to analyse the test data and present these reports to their customers. Both Lee and Azura attended Minitab Training and workshops run by Bizit Systems, Minitab’s Independent Licensed Reseller in Malaysia.
“The training from Bizit helped me understand how to apply certain statistical tools, and how to correctly interpret my data. The examples and data sets used during training were relevant to our work. My colleague learned tricks and tips that enabled her to use Minitab more efficiently and she was also introduced to the Macros function, which she uses to simplify our analyses and reporting.”
Lee also has become a Minitab enthusiast. “I like many things about Minitab. The interface is intuitive and the available tools are powerful and comprehensive. People who are new to Minitab can start with The Assistant menu which guides them to select the right tools and analyse their results.”
Using the type 1 Gage study, Gage R&R (crossed) Study and Attribute Agreement Analysis functions in Minitab, Lee and his team were able to assess the stability and repeatability of their test equipment.
“We reviewed the Contribution Table and Study Variation Table. The generated charts clearly displayed the sources of variability which helped us to determine the source of variation and take the appropriate actions to rectify this. That sometimes meant upskilling or retraining machinists, or carrying out preventative maintenance on our machinery.”
Run chart of P difference
The ability to measure and quantify the variability of their test equipment with Minitab before delivering it to the customer enabled i-Stone to streamline the equipment commissioning procedure. The easy application of this powerful analysis also has reduced the rework cost by $20,000 annually.
“As a system integrator involved in the fabrication of production machines, striving to achieve Gage R&R acceptance standards for test equipment is a challenging task. Using Minitab allows us to concentrate resources to improve the ways in which variation occurs.”
Lee also added that the satisfaction felt by customers has increased new business opportunities for i-Stone.
“Our customers are more convinced than ever that the equipment we deliver is of the highest quality, and we can support this with data, charts and graphs. We have a common understanding on variation and what is acceptable – we all speak the same language now!”