Issue link: https://iconnect007.uberflip.com/i/1489269
36 SMT007 MAGAZINE I JANUARY 2023 ing. Product design data has been fully digi- tized, comprising 3D-CAD data, bills of mate- rials (BOMs), and PCB layouts and specifica- tions for electronics assembly. From a layper- son's perspective, product data simply needs to be converted into instructions needed for the entire assembly operation to take place. Instructions are needed for automated pro- cesses, such as those assigned to machines and robots, as well as for human assembly opera- tors; all this is derived from product data. With product design tools and ERP systems already computerized, why is so much work still done manually? Back in the days of high volumes and limited product mix, manually compiling data worked fine. Today, there are many more product vari- ants, even customized product variants that require tailoring assembly at key operations. For example, each core chassis in a mobile phone has many thousands of active vari- ants. At the other extreme, variability is open- ended, such as the height of a bespoke piece of furniture, or the dimensions of a window blind. Humans can handle all this variation, but it takes time; a lack of automation coupled with an exponential increase in degree of vari- ation makes mistakes inevitable. In addition, people with essential skills are now leaving the manufacturing industry, and there's little moti- vation for new people to take on these stressful and repetitive roles for so little reward. Removing low-level and repetitive critical actions from manufacturing engineering is essential. With digital product data, manufac- turing engineering tools now have the oppor- tunity to elevate engineering's contributions. Although digital product design information has been available for some time, few opera- tions have set up the data flows necessary to handle it. Very few tools on the market have the built-in capability to use such data as their core driver, yet digital manufacturing engi- neering tools offer innumerable benefits, including the ability to quickly expose any exceptions or specialist requirements inherent in a design via the enhanced visibility provided by digital design data. New digital best prac- tices make it possible to automate processes associated with an individual product, includ- ing assigning product configurations, select- ing materials, and creating work instructions. Automating these processes helps limit opera- tional mistakes, defects, and delays. is effect of automation on the operation is not restricted to new products. Digital manu- facturing engineering allows risk-free, on-the- fly production allocation; these processes now take seconds as opposed to days. Engineering is now in the driver's seat, replacing the indi- vidual who, until now, has blindly pushed the car along the road. Contextualizing designs with data collected from the shop floor enables immediate decision-making, which improves operational effectiveness overall; low-level decisions are now made automatically. And because every data point is precisely con- sidered in the context of the design, variant, material, process, timing, etc., overall value increases. is all sounds great, doesn't it? However, most companies are not using dig- ital design data to automate their manufac- turing engineering processes. Company prof- itability and survivability are being compro- mised in lieu of IP security. Protecting IP is not new. e latest products from competitors are being physically torn down and their fea- tures, functions, and technologies analyzed in labs run by all the major product design teams. Today, there are many more product variants, even customized product variants that require tailoring assembly at key operations.