At a Glance:
- Toronto-based NeuronicWorks Inc. is a design engineering and manufacturing company that casts a Design for Excellence (DfX) lens over product development.
- DfX is a set of best practices intended to analyze the way a product has been designed with the intention of optimizing the product development cycle.
- Fundamentally about risk reduction, DfX should be inherently present in new product design, according to Titu Botos, CEO, NeuronicWorks Inc.
In business for 14 years, NeuronicWorks Inc. started out as a design firm. But three years ago, the firm pivoted towards manufacturing in order to offer clients “level zero to market,” particularly for those in industrial control and automation instrumentation industries, said Titu Botos, CEO of the Toronto-based design engineering and manufacturing company that specializes in the design, development and manufacturing of custom electronics and software products.
That shift demanded a greater focus on the scope of large production runs, as well as investing time and effort in thorough analysis of the product design and an ability to make adaptations before it moved to production.
The transition required Botos’ design and engineering team to be flexible and to consider more closely a product’s design in relation to its fabrication and manufacturability. The extra effort amounts to a small percentage of the overall cost, said Botos, whose team routinely filters product development through a Design for Excellence (DfX) lens.
READ MORE: A History of Design for Manufacturing and Assembly
What is DfX?
“These days, DfX is oftentimes used as a buzzword, as if it involves some rocket science and formulas,” said Botos. “In fact, it is a down-to-earth, concrete set of practices and knowledge about the capabilities of the manufacturing process.”
DfX is commonly defined as a set of practices that are intended to analyze the way a product has been designed with a view to optimizing production performance throughout the product development cycle. Stated simply, it means “knowing what machines are able to manufacture for you,” Botos said. “DfX is a guide for design, such that when the design blueprints are moved to manufacturing, you have few surprises, or fewer surprises.”
According to Botos, NeuronicWorks aims to deliver consistent, good quality design by taking into consideration previous experience and boiling this down to a checklist. When manufacturing companies develop guidelines or checklists against the DfX dimensions, he explained, they are able to produce higher quality products, reduce product costs, take advantage of shorter product development cycles, reduce risk and bring order to chaos.
“Design, by nature, is chaotic in that you have to come up with ideas to solve problems,” said Botos. “That’s the fun part of design.”
But in order to make sure that you produce good quality products and achieve the intended outcome that creative energy needs to be funneled through a filter. “The design phase starts everything and points the direction,” he noted. “There are many approaches to product design, but there are few ways to produce a good quality design again and again.”
Consider the “X”
DfX is both a framework and a practice to realize production. It is also an umbrella term, where “X” represents a set of criteria and can be substituted for reliability, assembly, serviceability, manufacturability, costs, supply chain, innovation, sustainability, reduced time to market…all dimensions that encompass better alternatives in an effort to achieve a competitive advantage and customer satisfaction.
Rather than take a hardline approach, Botos said DfX can be distilled into “simple, pragmatic down-to-earth set of rules and procedures that can be translated in a few checklists.” DfX is fundamentally about risk reduction, which should be inherently present in new product design, he said.
It is crucial for a design team to consider the X dimension early in the development phase, as decisions made during this phase drive the future of the product’s lifecycle. “An incorrect decision can cascade and multiply in the effort to correct it later on,” he said. In other words, by applying DfX principles at the design phase, and by encouraging collaboration between the design team, suppliers and manufacturing team, one de-risks the new product.
Design for Manufacturability
As industries move to greater automation, design for manufacturability and assembly is gaining relevance. Design for Manufacturability (DfM), is a closely related subset of DfX, which has as its objective to ensure that the design stays within the capabilities of the targeted manufacturing process.
This requires design engineers to create a risk mitigation and avoidance plan in order to understand what can go wrong, explained Botos. They would mitigate risk by developing an efficient process and minimizing product iterations by taking into account, for example, the use of fabrication or level of automation in the production. By following these rules and guidelines, he said, one can reduce the number of tools required in production and achieve shorter time to market.
Design for Certification
Designing to certification is often passed over as part of the design phase, according to Botos. He recalled having customers request specific designs, only to discover during the process that they had neither received certification nor passed safety standards in order to sell the product. Certification is fundamental at the start of the design, as is knowledge of the safety standards the product needs to comply with and what geographical markets the product will be sold to. “When a system influences lives, it has to be certified—that goes without saying—but it is overlooked,” said Botos.
Less Philosophy, More Pragmatism
The ultimate aim of DfX and its associated subsets—whether it is manufacturing (DfM), assembly (DfA), quality (DfQ) or supply chain (DfSC)—is to create a product that excels in each of these areas by making changes in the proposed design.
For Botos, building a checklist of what to look for “is not rocket science,” but de-risking the process does require experience and the emphasis may differ for each manufacturer. NeuronicWorks aims to produce the blueprints that will at once minimize product iterations and fit the production capabilities of the chosen manufacturer.
“For instance, you cannot ask for a more precision than the manufacturer is able to provide,” Botos said. “The point here is to understand clearly what your manufacturing partner is capable of doing, what machinery and automation they have. At the end of the day, somebody has to translate this information—the blueprints from the design phase—into the manufacturing phase. That is a process that is many times overlooked.”
It all calls for greater communication, Botos added. “I cannot say enough how many times it is overlooked.”
