How has technology impacted the product R&D process?

CAD software has become an integral part of the design process. It enables us to create detailed 3D models and simulate various design options, helping us refine the aesthetics, ergonomics, and overall performance of the ebike before physical prototypes are even built.

With some limitations and with human-end control, generative AI like ChatGPT can help to undergo a lack of technical skills or intuition in unpopular programming languages or unix tools. Sometimes helping high-level engineer to design not only more elegant solutions, but better ones based on AI inputs.

Computational Fluid Dynamics (CFD) modeling has helped us speed up the R&D process by modeling test outcomes based on prior measurements and allowing faster product development through replacing and assisting actual product testing.

With the infinite possibility of digital, the designers may tend to neglect prototyping, which may at the end reduce the "likeability" of a product, nothing can replace noise / touch and visual analysis of actual prototype even scale down. Do not neglect Design For X, DFX, Manufacturing / Maintainability / Assembly which can have an impact on the Total Cost of Ownership of the system.

3D printing has revolutionized the prototyping phase of ebike design. We can quickly create physical models of various components, such as brackets, mounts, or even entire frame sections, to evaluate their fit, form, and function. This rapid prototyping significantly shortens the development cycle and allows us to iterate and refine designs with ease.

Modeling and simulations on a specific design can spare more time to engineers than proofing prototypes and waiting for them to be out of the mould.

With the rise of data analytics, we can gather real-time feedback from users and apply it to product improvements. This iterative process helps us refine designs and deliver ebikes that better meet customer needs and expectations.

A lot of business and individuals have relied heavily on technology to help them with collaboration and communication. When we look back on the pandemic working remotely became a lot more common and even at the forefront of success for a lot of those who utilized this option. Other areas where technology has helped in a big way with collaboration and communication include global collaboration, data sharing, virtual labs (allowing data to be collected without physical presence), document/project management, and knowledge sharing. Technology has been the biggest catalyst in communication and collaboration but there's still a balance between leveraging technology for efficiency and addressing potential disruptions.

Technology has enabled us to incorporate sustainable practices into our R&D process. We can now design ebikes with recyclable materials, implement energy-efficient manufacturing processes, and reduce our carbon footprint.

Without risk there is no reward, but it's worth weighing the risks and making informed decisions before potentially going down the wrong path. Technology brings a few items of consideration to the table: Costs - There's always a cost associated with new technology whether it be a monetary value or time spent before there's a return on investment. Integration challenges - while a seamless transition is usually the goal, it's not usually the case. We must be prepared for the 'what if'. Learning Curve - Using new technology effectively and efficiently is not something that happens right away. The learning curve itself may affect normal production so it's something that needs to be carefully considered or prepared for.

Product lifecycle management software (PLM) greatly helps to manage products from concept all the way to retirement. This allows an organization to have better decision-making throughout the products entire existence. Smart products are on the rise. Products that are connected to the internet of things (IoT) are capable of collecting valuable data while also adapting their functions based on user preferences. Blockchain technology ensures the authenticity and traceability of products. This is extremely valuable in industries with stringent quality control requirements.

Technology has significantly transformed the product R&D process in food science. Advanced analytical tools and equipment have enhanced our ability to analyze and understand food components at a molecular level, facilitating precise formulation. Additionally, computational modeling and simulation enable predictive analysis, optimizing recipes and formulations. Overall, technology empowers food technologists to innovate, improve processes, and develop safer, more sustainable, and appealing food products.