Within a company’s Research and Development (R&D) team, you will find a diverse set of individuals from scientists and engineers to product managers and market researchers. Aside from the cross-collaboration within R&D teams, there is a heavy reliance on other departments such as manufacturing that plays a role in the steps a product takes along its way to market. R&D teams are the engine of innovation, driving progress within their organizations and shaping the future of tomorrow. Amongst the many challenges R&D teams face, the key to solving their problems lies in data. Let’s breakdown the intricacies within R&D and see how data analysis in Minitab makes these complexities manageable.
The research phase is the foundational pillar in the R&D process where innovative ideas are conceived and tested. To ensure the success of these endeavors, researchers rely on data analysis and statistics to navigate challenges and advance in their R&D journey.
Before any idea moves to market, researchers begin by translating customer needs into measurable product features. It’s where insights from market research are used to shape product development. This helps R&D to gauge what needs they must be able to meet to achieve success in the market.
Let’s look at an example using Minitab Statistical Software to better understand how data analysis can be used to validate product research. Your R&D team is looking to develop a new ultrasound imaging system. Two critical aspects of this new design are portability and image quality. You want to determine if there's a significant difference in user preference between machine designs.
Design and software engineers can use a 2 Proportions test to analyze the preferences of a sample of medical professionals for different attributes of the ultrasound systems. For example, they could present participants with scenarios where they have to choose between systems with higher image resolution but lower portability, and vice versa. By analyzing the responses, the 2 Proportions test can help determine if there is a statistically significant difference in preferences between the two design options. This analysis can provide valuable insights into which design direction to prioritize for further development.
After this initial market research testing, R&D can feel confident that they understand customer needs, but the further challenge lies in product feasibility. In other words, can the product be designed and built with existing technology to a standard that fits what the customers need?
Product feasibility is important for many reasons. When done properly in the research phase, engineers can spot potential risks and challenges to allow for proper resource allocation, saved time, and saved money. It demonstrates the viability of the product to give stakeholders confidence moving forward.
Turning back to our ultrasound example, we conduct a Design of Experiments (DOE) so that we can evaluate the device’s performance depending on multiple different factors. From our initial research, we know portability and image resolution are key factors to keep in mind when considering other factors.
To comprehensively investigate the impact of different materials on the ultrasound device, the R&D team employed a full factorial design. This approach involved systematically evaluating all possible combinations of three key factors: material (aluminum and plastics), wall thickness (two levels: thin and thick), and the presence or absence of reinforcing ribs. By testing each of these combinations, the full factorial design provides a complete picture of how these factors, both individually and in interaction, influence the device's performance. This thorough exploration will allow the team to gain a deep understanding of the design space, ultimately leading to the identification of the optimal combination of factors that meet the stringent requirements for portability, strength, safety, and accuracy.
Throughout these different steps, Minitab allowed researchers to maximize the impact of their work and cut costs before the product moves farther along the development journey. By empowering researchers to analyze data, test hypotheses, and optimize processes, Minitab contributes to the advancement of R&D teams early in their testing.
The development phase is crucial in translating research findings into tangible products and processes. This phase involves a rigorous process of design, testing, and reworking. To ensure product quality, reliability, and efficiency, development teams rely on data-driven insights. Minitab offers that comprehensive suite of tools needed to support engineers throughout their work.
Developers are looking to verify and validate that the proposed design is going to deliver the results they are looking for. In the development phase, the focus shifts to locking down the design specifications and manufacturing processes. Taking what the researchers have provided the R&D team with, engineers on the development end have the foundation they need to take the product across the finish line.
If we look at where we left the ultrasound imaging system, developers must answer the following questions:
“How can I ensure our systems are going to produce results within certain specifications?”
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“Can I be confident the product is going to perform how it is supposed to after it’s released?”
To assess the capability of the ultrasound imaging system’s manufacturing process, engineers can use Minitab's Capability Analysis tools. They can analyze the variation in key performance characteristics, such as image resolution, sensitivity, and accuracy, across multiple production runs. By comparing the process output to predefined specifications (ex. minimum acceptable resolution, maximum allowable error), engineers can determine if the process is capable of consistently producing systems that meet the required performance standards.
For instance, if the analysis reveals that the process is not capable, engineers can use Minitab to identify the root causes of the variation. This might involve analyzing process data to pinpoint specific steps or machines that are contributing to the variability. Once the root causes are identified, engineers can implement corrective actions, such as adjusting machine settings, improving operator training, or modifying the manufacturing process. By continuously monitoring and analyzing process capability data, engineers can ensure that the ultrasound imaging systems consistently meet the high standards required for medical applications.
To ensure the long-term reliability of the ultrasound imaging system, engineers can utilize Minitab's Reliability Analysis tools. They can perform life data analysis on prototype systems or components, such as the transducer or the battery, to estimate their expected lifetimes and predict failure rates.
For instance, engineers can use Weibull analysis to model the failure behavior of the battery. By analyzing data from accelerated life tests, where batteries are subjected to higher temperatures or voltages, they can predict the battery's lifetime under normal operating conditions. This information is crucial for determining the warranty period, planning maintenance schedules, and ensuring customer satisfaction.
Furthermore, Reliability Analysis can help identify potential weaknesses in the design. By analyzing the failure modes of prototype systems, engineers can pinpoint areas for improvement and implement design changes to enhance the overall reliability and durability of the ultrasound imaging system.
The journey of R&D is an ongoing cycle of learning and improvement. While research focuses on generating new knowledge and exploring uncharted territories, development translates these discoveries into market potential. By fostering a clear understanding of each other's objectives and leveraging insights from Minitab, organizations can ensure that research efforts are strategically aligned with development goals, maximizing the return on investment in innovation.