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The plastics processors discussing their priorities at several recent plant tours and industry conferences came from different regions and markets, but they all agreed on one thing: data-driven decision-making is essential for their success.

Of course, the success of data-driven decision-making depends on the manufacturing data available, as highlighted in a commissioned by Dassault Systèmes. Among manufacturers surveyed, 20% reported making bad decisions frequently 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 ´óÏó´«Ã½ improvements when manufacturing data was considered reliable and accessible.

Clearly, automated systems of data collection, recordkeeping, reporting, analysis and visualization are essential for plastic processors. Throughout the industry, enterprise resource planning (ERP), manufacturing execution systems (MES) and quality management systems (QMS) are broadly used for production planning, production monitoring and collecting quality control information. But what’s needed to take all this data and put it in the hands of the right people at the right time?

Conversations at plant operations and conferences point to three emerging tools that are being increasingly used to automate and centralize data collection, reporting and accessibility:

• Fully integrated ERP, MES and QMS systems that easily combine and share information across all the different manufacturing disciplines
• Dashboards visible throughout the enterprise that keep everybody informed about plans and progress
• Workflows and alerts that perform a watch dog role to keep processes flowing and identify bottlenecks

Integrated ERP, MES and QMS systems create companywide information networks which enable organizations to make data-driven decisions in real time. By replacing traditional seat-of-the-pants decision-making, tedious and error-prone manual recordkeeping, and disconnected information systems, they are empowering plastic processors of all sizes to improve performance across nearly all aspects of their operations.

Let’s look at two real-world examples of how plastics manufacturers are effectively making data-driven decisions to improve their ´óÏó´«Ã½es. We’ll then review seven pain points and how they can be addressed with better manufacturing data.

Case Study: Custom Plastics Manufacturer

One custom plastics manufacturer takes advantage of its comprehensive manufacturing ERP system to create low-code/no-code real-time dashboards and alerts to monitor production timelines and inventory levels, and get ahead of issues before they become problems.

Immediate access to production metrics helps the plastics processor to identify bottlenecks, adjust schedules on the fly and optimize resource allocation to meet deadlines. Meanwhile, real-time insights — delivered via dashboards — enable the company to quickly address any issues in the supply chain. The visibility gained through the dashboards and alerts enables the plastics manufacturer to proactively respond to production and supply chain issues before they turn into delays, improving customer satisfaction and strengthening relationships. As a result, the company has achieved on-time delivery rates nearing 100%.

Replacing traditional seat-of-the-pants decision-making, tedious and error-prone manual record keeping, and disconnected information systems can improve performance across all aspects of operations.

The plastics processor can monitor key performance indicators (KPIs), such as cycle times, downtime, quality metrics and delivery performance in real time. This, in turn, enables the manufacturer to identify areas for improvement, address inefficiencies and make more informed decisions.

Additionally, dashboards provide teams across the organization with real-time data, fostering ownership and encouraging collaboration. So, everyone — from shopfloor workers to production managers — has access to performance data that promotes faster decision-making and better problem-solving. This has instilled a shared sense of accountability while providing the greater team with the knowledge necessary to advance their skills.

Over time, more and more smart machines and robotics are being integrated into the plastics manufacturer’s production workflows. This equipment generates massive amounts of data that needs to be captured, monitored and reported. MES and dashboards are enabling the operation to accurately organize and report this information. This provides operators the data-driven insights they need to monitor, adjust and fine-tune the operations of these new highly automated systems.

Case Study: Polymer Tube Producer

A major Midwestern plastics processor makes polymer tubes for reagent test kits for bronchial infections. Because the tests are automated, they are highly dependent on the test tubes’ uniformity and sterilization. Production takes place in a secure clean room, and raw material is quarantined and inspected prior to production.

At the same time, processes throughout the plastics manufacturer’s operations are highly automated. Orders for test tubes are received electronically on an as-needed basis. The equipment that produces the tubes is fully automated and can produce 16 to 64 tubes in one cycle. The production equipment is fully instrumented for production and process monitoring to record variables, such as cycle times, temperatures and pressures. Additionally, all work center material handling is automated, and the parts are digitally inspected at four steps in the production process.

All this automation translates into a wealth of manufacturing data that empowers the plastics processor to make data-driven decisions across the organization.

First, because the sales orders arrive electronically, work orders are automatically created, and the number of cavities to run per cycle can be adjusted to meet the size of a particular order. Second, because the production cycle time is being measured, an update on the progress of the order through the work center is available at any time, along with a prediction of the completion time. Any delays are known in advance, and management decisions can be made to compensate for them.

Third, visual inspections catch part defects, and automated process measurements detect production variations — all in real time. Together, the two systems alert process engineering of production issues as soon as they happen, as well as route failed products to the scrap holding center. All the inspection and process data are immediately available in the statistical process control (SPC) module for root-cause analysis.

The arguments for data-driven decision-making are clear, but plastic processors are often derailed by a lack of integrated information systems.

Again, through production monitoring, the availability of finished goods is constantly updated so informed customer updates can be made. Similarly, raw material consumption is monitored, and purchasing is made fully aware of the timing requirements for additional materials inventory. At the same time, accounting is automatically updated on planned inventory investments.

The list goes on, but the point remains constant. The availability of manufacturing data leads to decisions based on factual, real-time information that enables the processor to strengthen its operations at every step of the way.

Seven Areas Improved by Better Manufacturing Data

We’ve seen two examples of how plastics processing companies are leveraging manufacturing data today to optimize decision-making and processes throughout the organization. Now let’s recap the top seven areas identified in the survey where manufacturers are using 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 but it also creates data for later use in SPC analysis and customer documentation.

Business Strategy (43%) — A foundational aspect of managing operations using ERP or similar systems is access to actual cost data, which can drive product and customer scorecards. It helps identify products that are most profitable, which products require price updates and which customers contribute most to the ´óÏó´«Ã½’ overall profitability — strategic information for managing a ´óÏó´«Ã½.

Customer Service/Support (36%) — Customers commonly ask, “When can I get my order?” The capable-to-promise feature of an ERP system looks at raw material, machine and labor availability, process and lead times, and competing schedules to give customer service representatives the information they need 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. Automatically tracking cycle times for both operators and machines provides management with runs-best information, which enables them to assign jobs to the people and work centers that perform them most efficiently.

Planning/Forecasting (33%) — Using sales orders to create work orders and scheduling those work orders to best meet expected delivery dates is a critical strength of manufacturing ERP systems. The same benefits are gained from forecasting, because knowing historical demand enables plastics processors to plan production in advance and ensure inventory is in stock to fulfill expected sales orders.

Project Management (32%) — In plastics manufacturing, not everything is a production run. Some tasks are projects like building tooling or installing a new machine. Project management systems excel at guiding and tracking these procedures step-by-step to completion. Just as importantly, they identify projects that have fallen behind schedule or exceeded planned cost.

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. This includes not only optimizing production schedules but also identifying resources that need to be expedited or expanded to prevent late deliveries.

Integrated Systems

The arguments for data-driven decision-making are clear and compelling, and the means to that end are often just as obvious. However, plastic processors are often derailed by a lack of integrated information systems. Some smaller companies end up thinking the technology is too complex for their ´óÏó´«Ã½ rather than a tool set to centralize recordkeeping and support decisions. Meanwhile, larger manufacturers often have too many best-of-breed solutions operating as data silos, preventing the end-to-end organizational view necessary for informed decisions.

Increasingly, successful processors of all sizes are demonstrating that comprehensive manufacturing information, made readily available, is a winning strategy that combines the best of industry expertise and data-driven decisions to optimize performance across nearly all aspects of their operations.

About the author: Steve Bieszczat is chief marketing officer for DELMIAWorks, where he is responsible for brand management, demand generation and product marketing. Prior to DELMIAWorks, he held senior marketing roles at ERP companies IQMS, Epicor and Activant Solutions. Bieszczat’s focus is on aligning products with industry requirements as well as positioning DELMIAWorks with the strategic direction and requirements of the brand’s manufacturing customers and prospects. Steve earned an engineering degree from the University of Kansas and an MBA from Rockhurst. Contact: 925-872-8863; Stephen.BIESZCZAT@3ds.com;