Production optimization sounds straightforward in theory. Plan and schedule efficiently, execute effectively, optimize continuously. Simple, right?

Anyone who has spent time on the shop floor knows better. Production optimization isn’t just about having the best scheduling software, best adaptive process control or the most automated equipment. It’s also about setting up appropriate synchronizations between every layer of your operations and enabling them to work synergistically – from sensors measuring temperature and pressure to executive dashboards tracking financial performance.

This synchronized intelligence is critical to closing the gap between planning and execution. It’s the blueprint that defines successful digital transformation in manufacturing today.

Gaps Preventing Production Optimization

Most manufacturers are running with significant blind spots that prevent them from responding quickly to market changes, promising more reliable delivery dates and improving margins considerably. These disconnects cost companies millions every year – and it’s completely preventable.

The S&OP team creates demand plans and capacity allocations based on market forecasts and strategic priorities. The S&OE team makes daily decisions based on immediate constraints – equipment availability, materials and components inventories, quality issues. If these teams don’t frequently synch up, they will spend most of their time firefighting to meet misaligned commitments.

The S&OE team creates production schedules based on thousands of master manufacturing data points (assumptions related to equipment performance, processing times, raw materials lead times, yields, etc.) residing in the company’s ERP system that rarely get updated. Meanwhile, a specific reactor on the shop floor has been running 15% slower than spec, a raw materials supplier just delayed a critical shipment by a couple of weeks, and cleanouts have been taking 50% longer because new operations personnel are being trained up. Inaccurate and unachievable schedules result in the manufacturing team second guessing the S&OE team and put at risk the commercial team’s ability to set realistic order commitment expectations with customers.

Each team is looking at their area in isolation:

However, everyone is missing the “bigger picture” that could unlock significant value for the business. For example, knowledge of the current production status compared to the published production schedule allows the S&OE team to adjust for delayed operations and enables the commercial team to proactively reach out to customers to give accurate updates regarding order shipment expectations.

Most equipment failures are treated as external disruptions rather than predictable events that can be managed proactively. When a piece of equipment goes down unexpectedly, it creates a domino effect: delayed batches, missed customer commitments, overtime costs, expedited shipping costs. Downtime is inevitable; however, it is better to have it proactively planned – with alignment across maintenance, S&OP and S&OE teams and visibility to consequences – rather than being reactive to unplanned downtime. 

Teams spend enormous effort manually reconciling what was planned versus what happened. By the time they figure out the gaps, the window of time available to optimize has passed.

These gaps aren’t just operational inefficiencies – they are digital transformation barriers that prevent manufacturers from unlocking the full value of their technology investments.

The Digital Transformation Blueprint: Synchronized Systems Intelligence

True digital transformation in chemicals manufacturing isn’t just about implementing individual technologies – it’s about creating synchronized intelligence across systems that share common data at the intersections of work processes and enabling them to work together synergistically.

Production optimization happens when S&OP, S&OE and manufacturing operations systems synchronize, transforming periodic planning to continuous optimization and alignment across teams – allowing to adapt to changing market conditions while maintaining strategic alignment. When a key customer accelerates delivery requirements or operations are running slower than expected, synchronization gives your company a competitive advantage through superior responsiveness, proactive customer service and an understanding of decision-making tradeoffs and consequences.

Example of synchronized intelligence in action: When adaptive process control (APC) systems like AspenTech DMC3™ and Aspen Process Sequencer help to automatically calibrate master manufacturing data used by a production scheduling system like Aspen Plant Scheduler™ based on actual equipment performance, the scheduling system becomes more accurate, which improves customer promise reliability, which in turn, enables sales to bring in more revenues and grow market share.

Production optimization happens when equipment health data flows into planning and scheduling systems so that it becomes a variable rather than a surprise disruption. This means manufacturers can optimize predicted issues rather than react to unplanned downtime. Manufacturers can intelligently determine the best time for planned downtime while considering existing customer order commitments.

Example of synchronized intelligence in action: When prescriptive maintenance systems like Aspen Mtell^® can provide 30 to 90 days lead time on equipment failures and automatically send alerts to a scheduling system like Aspen Plant Scheduler^™, it can then be used to determine the better or best time for taking planned downtime while minimizing the impact to existing customer commitments.

Production optimization means that manufacturing execution results (actual transition times, actual setup times, actual cleanout times, actual yields, actual equipment performance, etc.) automatically feed back into planning and scheduling systems, making these systems better over time. Each production run or campaign improves the accuracy of future plans and schedules. It also means that everyone needing real-time visibility and notifications related to the “bigger picture” gets what they need.

Example of synchronized intelligence in action: When an industrial data fabric like AspenTech Inmation^™ helps to intelligently synchronize other systems like Aspen Production Record Manager^™ and Aspen Schedule Explorer^™, everyone has visibility and notifications in situations where actual operations are running late compared to schedule, schedules can be proactively updated and communicated, commercial teams can proactively notify customers about their updated shipment details, and the overall company strengthens its market reputation related to providing an exceptional customer service experience.

Companies that execute this blueprint respond to market changes faster, promise more reliable delivery dates, and operate at margins competitors can’t match.

Your Digital Transformation Roadmap Starts Here

The goal isn’t just connected systems – it’s synchronized intelligence between every layer of your operations and enabling them to work together synergistically.

Every week you delay this transformation, someone else in the chemicals industry gets ahead. They are turning data into competitive advantage. They are enabling synchronized intelligence that multiplies the value of their technology investments.

The manufacturers thriving five years from now won’t be those with the most advanced individual technologies. They will be the ones who orchestrated all their technologies into synchronized intelligence. The only question is whether you will lead it or be forced to follow.