There is now broad consensus that data-driven decision-making is essential to success in today’s highly competitive manufacturing environment. Customers’ price-consciousness, combined with demands for quality and on-time delivery, leave little room for error and seat-of-the-pants measures. Instead, well-run manufacturers increasingly rely on insights from operational systems across the front office and shop floor to make better-informed decisions.
Despite wide acceptance of data-driven manufacturing principles, 20% of the manufacturers participating in a recent survey commissioned by Dassault Systèmes reported making bad decisions on a frequent basis because of data they did not have, did not trust or did not have access to. By contrast, the same survey found 15 key areas—ranging from quality control to production efficiencies to sales—where 70% or more respondents reported significant business improvements when manufacturing data was considered reliable and accessible.
End-to-end control and visibility of the manufacturing cycle, from sales order to shipment, requires filling the data gaps that often exist between front-office planning operations and actual production execution, quality assurance and, ultimately, warehousing and shipping operations. The key to success is not only planning well, but just as importantly, being aware of when production delays and quality issues have thrown plans off course. So, the necessary information is immediately on hand to take corrective action and prevent manageable problems from cascading into significant delays.
For instance, SAY Plastics uses a combination of dashboards, advanced production tracking, and alert systems in its enterprise resource planning (ERP) system to monitor production timelines. Immediate access to production metrics help SAY identify bottlenecks, adjust schedules on the fly, and optimize resource allocation to meet deadlines. Meanwhile, real-time insights delivered via dashboards and alerts, enable the company to quickly address any issues in the supply chain. As a result, SAY Plastics has dramatically improved its on-time delivery rates, which are now near 100%.
In the survey, two of the largest reported gaps were in production performance and quality control. These are two areas where it is not unusual to find isolated management systems that are decoupled from the business’s primary manufacturing operating system. Closing these data gaps requires integrating the results from production monitoring, process monitoring and quality inspections into the information flow that informs the front-office planning and customer relations teams so they can maneuver through the inevitable twists and turns of daily production.
SIGN Fracture Care, an FDA-registered and ISO 13485-certified medical device manufacturer, offers a good example of how to close the gap between quality control and the rest of the organization. As a highly regulated company, having properly calibrated inspection equipment supported by rigorous documentation is fundamental to quality inspections.
Previously, manual inspection processes at SIGN produced more paperwork, requiring more double checks and resources than perhaps any other processes in the business. However, ISO 13485 and FDA auditors prefer evidence-based audits over the older narrative-based format, so ready access to comprehensive device history records has become critical to maintaining regulatory compliance. In response, SIGN has automated its processes by using the ERP system’s quality modules to trigger and document all inspections as well to schedule and document all of its gauge calibrations. Now all the storage is digital, and inspection data is immediately available.
In-line quality inspections also serve to validate the acceptability of work in process as it progresses to finished goods. Production and process monitoring play a central role in supporting these inspections. Production monitoring tracks a work order’s progress through the production phase. Meanwhile, process monitoring verifies whether tooling and equipment are performing to specification.
Without real-time production, process and quality information, planners often find themselves unknowingly scheduling jobs and materials into work centers that are still occupied with a prior production task. One problem is then compounded by the arrival of a soon-to-be second problem. By contrast, creating a closed information loop that bridges shop-floor results and front-office software enables planners to realistically schedule the utilization of equipment, materials and labor.
The demand to create a closed loop across the shop floor and front office is why so many manufacturers are focusing significant operational and information technology efforts on connecting their ERP, manufacturing execution and quality assurance—either through systems integration or adoption of platforms with native integration of these disciplines.
Five Examples of Closed Loop Data-Driven Decision-Making
Let’s review five of the top areas identified as data deficiencies in the Dassault Systèmes survey where manufacturers are using integrated planning, production and quality data to improve their performance.
Quality Control (47%) – An excellent example of data-driven quality control is in-process inspections, which are forced by the quality control module. Operators (or automated equipment) record periodic measurements. If a measurement fails to occur, supervisory personnel are notified. This not only catches defects before they become systemic; it also creates data that can update the ERP system on production constraints and any impacts on product delivery. Additionally, the data can be used later in statistical process control (SPC) analysis and customer documentation.
Business Strategy (43%) – A foundational aspect of managing operations using ERP or similar systems is gaining access to actual cost data, driven in part by shop floor process and production monitoring, to produce product and customer scorecards. This helps to identify the products that are most profitable, what products require price updates and which customers contribute most to the business’ overall profitability—strategic information for managing a business.
Customer Service/Support (36%) – A frequent customer question is, “When can I get my order?” When the capable-to-promise feature of an ERP system aggregates up-to-the-moment data from inventory and production software—such as raw material and consumption rates, machine and labor availability, process and lead times, and competing schedules—it can give customer service representatives the information to provide fact-driven delivery time frames to customers.
Operator Performance (34%) – Not all operators perform the same task at the same rate, nor do all machines. Using production and process monitoring to automatically track cycle times for both operators and machines and feed this information into the ERP system provides management teams with accurate runs-best information. This empowers them to assign jobs to the people and work centers that perform them most efficiently based on hard data instead of gut feelings.
Order Management (32%) – Multiple orders often compete for inventory and production resources. ERP systems automatically sort through the constraints and identify a best path forward. When the ERP system is populated in real time with data from production and process monitoring, quality inspections, inventory management, and supply chain management, manufacturers are empowered to not only optimize production schedules but also identify any resources that need to be expedited or expanded to prevent late deliveries or costly rush delivery fees.
Too many manufacturing businesses still face information gaps caused by error-prone manual record-keeping and disconnected information systems. Lacking access to data they can trust, these companies continue to fall back on traditional seat-of-the-pants or gut-level decision-making. By integrating production and process monitoring, quality management, and other operational systems into company-wide, closed-loop information networks, manufacturers gain the power to make data-driven decisions in real time and improve performance across nearly all aspects of their operations.
