Issue link: https://iconnect007.uberflip.com/i/1500520
62 SMT007 MAGAZINE I JUNE 2023 Exacerbating this are machine vendors themselves that are selling data collection and analytics tools that only address their specific operations—disconnected islands of data per- petuating the need for engineers to waste valu- able time manually aggregating it into ad hoc spreadsheet tools. At least 80% of engineering time is wasted on manually aggregating and cleaning up data 1 . ink about what this 80% is costing you in pure dollars, time to market, and more. e solution is to implement a modern trace- ability soware system that automatically cat- alogs and contextualizes data from every test and assembly operation across the entire line. Interpreting and storing data from all the differ- ent formats and protocols is a complex under- taking, and so best suited for modern soware built on web-scale technologies. is breed of soware can be configured to be format and protocol agnostic, able to capture all requi- site data from all machines, whether it's file or network HTTP/HTTPS data interchange. It will catalog and contextualize it in real time for immediate data-driven insights. Don't get locked into machine vendor spe- cific data collection solutions—they are just another data silo. Above all, avoid legacy solu- tions providers; they are still sitting atop so- ware written decades ago, based on older approaches to manufacturing that result in costly customizations, technical debt, and the inability to scale without more costly upgrades. Modern solutions using web scale technolo- gies are the future because they require lower support costs, plug-and-play type data con- nectivity via APIs (application programming interfaces), and enable enterprises to be nim- ble and adaptable amidst the growing com- plexity of today's supply chain markets. What are the common misconceptions with data collection and data management? e first misconception is that it's complicated and costly, therefore only accessible by large corporations who can afford to spend hun- dreds of thousands of dollars on the endeavor. Data collection and an effective data man- agement system are a fairly straightforward and cost-effective endeavor to take on. You just need to roll up your sleeves and audit the data collected at every step and every machine in your factory line. Look at where the gaps are against the overall production traceability requirements, so that you have a full picture of the needs. Now you'll be armed to find the right data collection and traceability soware solution. e second misconception is that you should start small, such as with only one machine cell, and that this will somehow translate and scale to the rest of the factory line. e biggest (and oen the costliest) miscon- ception is thinking your ERP can somehow be made to double as the factory data collec- tion and traceability system. Not even a Net- suite Oracle system out of the box can do seri- alized traceability, let alone track the 30+ pro- cess steps of an SMT production line. ERP is based on a general ledger architec- ture, not a factory data collection and manage- ment architecture. Bring in a system such as an MES (manufacturing execution system) to provide you with true factory line level visibil- Ryan Gamble