specifications on a custom work order . Access to information keeps production lines moving as planned , with minimal interruptions because of questions , disconnects between departments , or stockouts .
Advanced analytics can go even further to keep the shop floor operating smoothly and profitably . Managers can delve into exceptions and track influencing variables . They can find opportunities for improvement , such as eliminating quality roadblocks or controlling down time .
PRACTICAL APPLICATIONS As artificial intelligence ( AI ) and machine learning ( ML ) have moved into the mainstream , manufacturers are increasingly seeking practical applications for data insights . Proof of concept projects are being replaced by ones which promise a timely , measurable return on investment . The shop floor offers many practical applications for AI-driven insights . Routine processes can be automated , streamlining the need for human interaction . Only anomalies or exceptions need to be routed to supervisors for individual attention . Streamlining the data flow will also help keep various teams apprised of real-time updates and needs . No one is out of the information loop , falling behind on evolving expectations . One data-driven digital thread will connect every stage in shop floor operations .
Here are nine examples of how democratised data helps boost productivity :
1 . Custom quotes and bill of materials . Efficiently managing make-to-order , engineer-to-order , and configured products requires an automated system for generating rules-based quotes and matching bills of materials . Once the customer has approved the order , the specifications must flow from sales to operations to ensure the right dimensions , features , and finishes are applied . Access to the customer order helps managers verify details , eliminating reworks or customer returns .
2 . Projecting raw resources needed . Synchronising production planning and availability of raw resources requires access to data and AI-driven predictive capabilities to prevent stock-outs . Data helps procurement managers make sure the warehouse is stocked with necessary components . Too much inventory can be just and dangerous , tying up capital and risking obsolescence .
3 . Accurate scheduling . Synchronising production runs to fulfill customer orders depends on accurate account data as well as sales , delivery promises , inventory of raw materials , and machine capacity . Working with co-manufacturers or subcontractors also requires access to information . Collaboration portals can help share information while protecting security .
4 . Strategic scheduling of the workforce . With data insights , managers can track and understand performance of shifts and crews , identifying essential staffing requirements and tracking expenses . With the acute labor shortage manufacturers face today , careful scheduling of right-skilled workers is especially important .
5 . Workflows . Keeping operations running smoothly with no gaps , delays , or roadblocks requires coordination among teams and sharing data on job status , equipment performance , and scheduling . Reporting can help identify trends and analyse variables , allowing managers to delve deeper into influencing factors that can be improved . Decisions can be made , changes executed , results monitored , and further refinements made . Continuous improvement can be part of the system and standardised workflows .
6 . Compliance and quality control . Managers need to track , monitor , and evaluate quality standards , with a continuous feedback loop in place . As new products are introduced , specifications need to be easily updated and accessible to relevant teams . Regulation compliance , too , is critical in many industries and demands accurate reporting . Democratised access to data helps keep the details in view when and where they are needed most .
7 . Waste reduction . As manufacturers strive to be more sustainable , they place a high priority on reducing waste , including energy , water , and raw resources . Reducing scrap is essential . By improving consistency and quality control , fewer units will need to be scrapped or reworked . Access to data will help crews verify proper machine settings , consult knowledge banks for typical resolutions of issues , and verify proper specifications and variables .
8 . The call centere . The aftermarket service operation needs real-time access to account and product details to answer customer questions about deliveries , service agreements , warranty status , and scheduled preventive maintenance . Service dispatch needs to access the location and availability of technicians to dispatch the right person to the right job based on geography , service level agreements and urgency .
9 . First-call resolution . Field technicians at the job site need remote access to details on the unit , as-serviced history , inventory status of parts , and availability of replacement or upgrade units . A technician with the right data is seen as a trusted advisor and can often make sales in the field .
www . infor . com / en-gb
19