Four Strategies for Optimizing Production Scheduling in Real Time

By Ed Potoczak, director of industry relations

In a recent conversation, an executive at a South Carolina-based injection molding and vacuum forming manufacturer described how the company culture has evolved to enable greater operational performance and efficiency while increasing employee morale. The gains are the direct results of automating the company’s real-time monitoring of production processes, tool maintenance and inventory counts to give the company timely, accurate information. Not only is this enabling swifter, better management decisions in each plant, it has led to greater teamwork, more engagement from all associates and a continued focus on “let’s decide now.”

Notably, the company’s evolution has enabled it to optimize production scheduling in real time – a critical factor for ensuring the quick turnarounds demanded in today’s market. In fact, 57 percent of manufacturers participating in a recent survey conducted by IQMS stated that having short-notice production capabilities was the value-added service their customers appreciated most.

This article examines how plastics manufacturers can adopt four strategies for optimizing their own production scheduling in real time to enable short-notice production and improve overall performance.

Providing visibility into real-time data and metrics

The driving factor underlying a transformation toward production agility is the real-time availability of data and metrics across each area of the business. For example, at the South Carolina-based manufacturing firm, multiple monitors in central kiosks on the floor give hourly workers, technicians and managers immediate access to actionable insights regarding equipment status, product quality, materials, tooling availability, sales demand changes and work order priorities.Shared, real-time access to information empowers operators, technicians, schedulers and managers to form quick huddles when necessary, so everyone affected sees relevant information and can decide together what to do next. Because employees are working with the same version of the truth, including any factors that might impact execution of planned production, they become comfortable with in-the-moment decision-making. This serves to streamline the scheduling process, make set-ups more efficient and maximize production capacity. Additionally, the team can minimize the wasted value of making a nonconforming product and reduce unplanned interruptions caused by relying on postmortem reporting.

A key aspect of timely visibility is implementing a short, closed feedback loop in real time to gain actionable insights to help improve uptime and utilization of production equipment. When a parts maker automates the capture of operations data from production machines, inspection equipment and tooling, it is possible to process and display metrics on cycle time, production counts, scrap reporting and overall equipment effectiveness (OEE) as well.

Oversight can be extended further by integrating automatically captured equipment measurements with statistical process control (SPC) tools to predict equipment and quality issues before a failure arises. This use of automated SPC avoids gaps and outright mistakes in the source data and helps to prevent skewed analysis. Using key characteristics to be monitored, control limits and level of control (such as Six Sigma) – established by plant operations and quality specialists – the analytic software can alert key personnel when a parameter starts to trend out of control. This enables proactive adjustments and maintenance, if needed, to assure product quality with minimal disruption to production.

Implementing finite capacity planning

In almost every production setting, scheduling is best done in real time. For example, a Midwest automotive interior parts supplier that deals with complex Electronic Data Interchange (EDI) order and releases relies on a planning and scheduling system to support its fast-paced environment. The system tells the team what needs to be running, what will be scheduled tomorrow, what materials need to be received and on-hand for that schedule to function appropriately and, most importantly, what future orders the scheduler should enter for the variety of raw materials that will be needed. Importantly, this guidance is based on timely information about resins, work center status, readiness of molds and output containers, and maintenance plans to ensure maximum utilization.

If a manufacturer’s business model involves high-volume, repetitive production or has a very short manufacturing cycle time (i.e., minutes to hours), scheduling can be done with unlimited capacity presumptions. This type of base logic can be executed with classic materials requirements planning (MRP), production requirements planning (PRP) calculations or Kanban visual/virtual “card” methods.

However, in high-mix/low-volume situations or where process equipment has very specialized capabilities, the flow of product through these processes needs to be planned more precisely. This must be done to address the availability of specialized materials and variable throughput based on the number and complexity of the tasks to be performed at each operation. Optimizing the mix of materials by machine to reach optimal output levels in these scenarios requires finite scheduling applications and workflows.

Modeling finite (real) capacity constraints is the foundation for optimizing production performance across the shop floor, as it takes into account every quantifiable source of variation in production efficiency. These factors typically include:

  • required training levels,
  • machine health and OEE levels,
  • stability and reliability of work order instructions and operations for production machinery,
  • the calibration requirements of tools to reach optimal levels and
  • fine-tuning of algorithms for the specific output goal of a given production run.

By taking into account all of these considerations, machinery will require less retooling for specific product runs. This, in turn, minimizes set-ups and teardowns, enabling more work to get done in less time on the production floor.

Examples of these kinds of machines are automated insert molding machines with robotic material handling, paint and powder coating systems and computer numerical control (CNC) machining centers, among others. Finite planning and scheduling enable operations planners to use “what-if” scenarios to fit shifting demands into every bit of processing time available over the following days and weeks to maximize output while following validated processes. This approach can provide useful insights into what “available to promise” as well as “capable to promise” commitments manufacturers can keep, along with capacity for additional business.

If the scheduling software has the sophistication and efficiency to process schedule updates in real time, manufacturers may apply finite capacity constraints for some of the production floor and then apply classic flexible capacity methods for the rest. This hybrid plan can enable the best of both approaches, depending on the nature of the workflow through different parts of the plant.

Automating equipment maintenance

Plastics manufacturers should consider automated machine and tooling maintenance schedules in their scheduling calculations and visual screen cues. This enables production scheduling specialists to avoid the downtime associated with waiting to get current status information or even actual time for the maintenance to be performed. Additionally, planners and managers can quickly adjust work order priorities as they orchestrate the use of alternative equipment where possible or carefully postpone set-up work, which can be wasted if done before the work stoppage.

Companies also can take a cue from a Great Lakes injection molder that has streamlined maintenance activities in its three facilities by using machine and tooling maintenance schedules based upon actual run times and cycle counts, not arbitrary standard day counts. The company piloted machine monitoring in stages, starting with a couple of work centers in one plant with smart sensors on older machines and direct connections to controllers on newer ones. As the team gained experience analyzing the data in real-time metrics and dashboards, they refined their focus to the few key measurements that reliably indicate equipment health. This has helped prevent unexpected disruptions. It also saves time and money by eliminating unnecessary maintenance work because plant engineers can refine preventive maintenance schedules for equipment that proves to be more durable and reliable than expected.

Maintaining production history records

Last, given the intense focus on consumer safety and regulatory compliance in many industries, manufacturers may need to establish production history records (PHRs) in databases that allow rapid recall and analysis of past production activities. It would be cost prohibitive to capture this information manually in sufficient detail to quickly satisfy inquiries from customers and regulatory agencies. In addition, it could introduce the risk of errors.

Therefore, companies will want to invest in integrating Internet of Things (IoT) technology with their software for managing PHRs to provide instant feedback and historical process detail. Key benefits of this smart, connected approach to manufacturing include robust product traceability, 100 percent accurate inventory tracking and the ability to engage mistake-proofing logic in the set-up of production jobs. These best practices are easier for manufacturers of all sizes to establish and sustain today, as sensors with increasing capabilities and declining costs are coming onto the market.

With modern, affordable operations technology to streamline the electronic capture of critical information needed for smart real-time scheduling, production monitoring, maintenance and quality measurement, plastic parts makers have the potential to increase their utilization of production assets and resources on a consistent basis. And, that translates into the ability to deliver on the predictable short-notice production capabilities key to attracting, retaining and growing customers in today’s dynamic manufacturing market.

Ed Potoczak, director of industry relations for IQMS, brings extensive expertise in manufacturing and engineering. He is currently a Manufacturing Enterprise Solutions Association (MESA) Americas board member, participating in the Smart Manufacturing working group. He also is certified in Design for Manufacture and Assembly and Value Analysis/Value Engineering. For more information, visit