Nine ways consumable , democratised data improves factory operations
SOFTWARE & SYSTEMS SMART MANUFACTURING
INFOR
Nine ways consumable , democratised data improves factory operations
Manufacturers are increasingly turning to smart manufacturing principles , hoping to turn the shop floor into highly efficient , data-driven operations humming with synchronised precision . Unfortunately , lineof-business managers , team leaders , and shift supervisors — the shop floor heroes — often lack easy access to the ERP system and the relevant data needed to keep production on track .
Deskless workers play a vital role in operational efficiency . Democratising data — making data consumable for a wider population — will give these frontline users valuable decision-making insights . With role-based dashboards and reporting tools , they can drive better performance up and down the production line , from smart use of resources to reduction in rework and scrap .
Countless critical decisions are made on the shop floor every shift . The setting — notoriously noisy and fast moving — isn ’ t conducive to careful , prolonged pondering of influences . Fast-moving production lines require fast decisions and expedient action . At the same time , errors can be costly , eating away at profitability , wasting resources , and jeopardising aspromised delivery times . Decisions based on guesses , one random exception , or anecdotal stories can send a team into spirals of wasted time , frustrating workers and managers alike .
EMPOWERING FRONT-LINE USERS
The answer is to put data in the hands of every decision-maker in the organisation , even those who aren ’ t advanced data analysts with skills in report writing and applying artificial intelligence ( AI ) algorithms . Modern digital platforms provide interface tools to help users apply advanced functionality to everyday situations . Featuring low-code and nocode capabilities , the digital platform provides front-line users with rolebased dashboards to track relevant key performance indicators ( KPIs ) and custom reporting to investigate emerging trends . Quickly , dynamic insights are within reach of machine operators , maintenance technicians , and material handling engineers , scheduling clerks , and shift leaders .
DATA DRIVES SPEED AND ACCURACY
Operational-level access to data is especially helpful in preventing gaps in workflows and avoidable delays . Frontline workers can get immediate answers to design questions or 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 datadriven 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 .
130 PECM Issue 62