Issue link: https://iconnect007.uberflip.com/i/1502623
30 SMT007 MAGAZINE I JULY 2023 lect and contextualize data. is provides infor- mation which engineers can use to orchestrate any supporting or corrective actions that may be required. A Different Kind of 'Interface' e same paradigms I've detailed are used for automation and are relevant for manual assem- bly operations which represent a different kind of "interface" to gather data. Rather than using traditional work instructions as a refer- ence, electronic work instructions are interac- tive, conduct the active operation, and detail step-by-step activities throughout. Data is col- lected and confirmed, such as the start and end times of each task and activity, as well as excep- tions that may occur, all in a way that the oper- ator can qualify and contextualize. One exam- ple is the consumption and spoilage data of materials, which allows for Lean material man- agement and quality data for analysis. Smart tools, such as torque wrenches, electronic rul- ers, scales, etc., that are being integrated into the operation then automate that collection of measurement data. Manual assembly oper- ations become as "smart" as automated pro- cesses. AI-based analytics gain the same qual- ified information from manual assembly sta- tions as from automated. Use and analysis of contextualized Smart fac- tory data becomes common across the whole manufacturing floor. Functionalities and bene- fits of Lean material management, active qual- ity, and adaptive planning are applied in a com- parable and interoperable way. Advanced AI- based analytics have the same opportunity to provide insight and assessment of opportu- nities for improvement, and reaction to chal- lenges, be they restrictive or opportunistic. e de facto rule of manufacturing qual- ity has always been that if a human "touch" is involved, there will be defects. is rule applies ubiquitously around manufacturing. With the automation of data collection, there is unifor- mity in contextualization, treating all stations as equals, visibility, reaction, and control; the human touch is taken out of situation assess- ment and focused on actions and outcomes. Manufacturing becomes more dynamic and controllable, with reduced dependencies on deep-dive skills. is reduces downtime and increases productivity and quality. Machines, people, and AI have, for some time and will always now be, elements in our manufacturing equation. Let's have them work together in harmony, to deliver our best busi- ness results. SMT007 Michael Ford is the senior director of emerging industry strategy for Aegis Software. To read past columns, click here.