Following several acquisitions, leadership wanted to optimally leverage its investments at the company’s primary Americas production facility, the No. 1 production site in the region. The objective was concrete: increase plant throughput 30% using existing technology while improving asset utilization and inventory management. That was an ambitious target for a site producing 76 different product families and considered one of the most complex in both the company and the industry, with 80% of its output in extended-release products competing for limited machine groups across multiple intermediate processing stages.
At one of the industry's most complex sites, POWERS built a quarterly rhythm-wheel schedule covering 93% of products by volume in five weeks, turning a plant that scheduled work on equipment availability alone into one that finally knew its true capacity.
Global Specialty Pharmaceutical Manufacturer
Results at a Glance
93%
Products Scheduled
5 weeks
Time to Deliver
Executive Brief
The plant scheduled and ran work on a 7-day cycle based on equipment availability alone, with cycle-time expectations unknown, cleaning operations disconnected from the schedule, and ERP standards that did not match what production personnel reported, leaving true capacity an open question against a goal of 30% higher throughput on existing technology. POWERS applied an Integrated Management System approach, taking a floor-level look to find the gaps and then tying them back to the existing information systems, and designed a 90-day rhythm-wheel production schedule supported by demand simulations, standard work, asset utilization metrics, and a product-level implementation roadmap. The quarterly schedule accounted for 93% of products by volume at the primary Americas site, and the full model was delivered in five weeks.
The Situation
A plant that ran one of the industry's most complex product mixes on a 7-day cycle set by equipment availability, with no real read on its own capacity.
Following several acquisitions, leadership wanted to optimally leverage its investments at the company’s primary Americas production facility, the No. 1 production site in the region. The objective was concrete: increase plant throughput 30% using existing technology while improving asset utilization and inventory management. That was an ambitious target for a site producing 76 different product families and considered one of the most complex in both the company and the industry, with 80% of its output in extended-release products competing for limited machine groups across multiple intermediate processing stages.
Beneath the goal sat a structural problem. Work was being scheduled and performed on a 7-day cycle based simply on equipment availability, with no defined standard work for machine setup and cleaning, and cleaning operations that were not linked to the production schedule at all. Cycle-time expectations were unknown or uncommunicated on processes that ran as long as 96 hours, and there was no process to compare elapsed against appropriate cycle times. Compounding all of it, multiple IT data platforms generated reports that did not necessarily reflect what was happening on the floor, and the standards in the ERP system did not match what production personnel reported. True capacity was effectively unknown.
Leadership needed to determine the plant’s actual capacity, develop an optimal rhythm-wheel schedule, and link those disparate systems back to supervisory behavior, skills, communication, and decision-making. This was not a one-time fix. It required a structured production schedule built on correct standards, operating procedures, and behaviors, along with a defensible answer to whether the operation could absorb 30% more volume at all.
The Diagnosis
Six structural gaps producing the same outcome from six directions.
Scheduling driven by equipment availability alone
Work was scheduled and performed on a 7-day cycle based simply on what equipment was free, with no structured production schedule. Without a planned rhythm, sequencing was reactive and there was no foundation for raising throughput predictably.
Cleaning disconnected from the schedule, no standard work for setup
There was no defined standard work for machine setup and cleaning, and cleaning operations were not linked to the production schedule. Time-consuming changeovers and cleanings happened outside any plan, eroding available capacity in ways no one could account for.
Cycle times unknown and never checked
Cycle-time expectations were unknown or uncommunicated, and there was no process to compare elapsed against appropriate cycle times, on processes running as long as 96 hours. Long runs could drift well past expectation with nothing flagging the loss.
ERP standards that did not match the floor
The standards used in the ERP system did not match what production personnel actually reported. Planning and master data were built on numbers the operation itself did not recognize, undermining every downstream schedule.
Inconsistent data hiding true capacity
Multiple IT platforms generated reports that did not reflect what was happening on the plant floor, and data was inconsistent across systems. With no reliable single picture, the plant's true capacity remained unknown.
No confidence the plant could absorb 30% more volume
It was genuinely uncertain whether operations could accommodate 30% higher volumes across 76 product families, 80% of them extended release, at one of the industry's most complex sites. Leadership had a target but no validated basis to commit to it.
What POWERS Did
Designed a quarterly rhythm-wheel schedule and made the plant's true capacity visible.
POWERS used an Integrated Management System approach, taking a floor-level look to identify the gaps and then tying them back to the existing information systems. The scope was to develop a 90-day rhythm-wheel production schedule that could be replicated at other high-velocity plants. POWERS modeled actual production equipment capacity against the demand timeline using the rhythm wheel, supporting an Infor Advanced Planning and Scheduling implementation, and ran simulations based on average weekly demand to validate that the schedule supported market requirements.
In parallel, the team established inventory requirements for low-running products so they would protect capacity for the high-running ‘A’ products, freeing capacity in the process, and defined optimal product inventory levels to sustain high customer service. POWERS created standard work sequences for all products at all stages, including setup procedures, run parameters, and cleaning specifications, and developed the standard operating procedures and required behaviors for future master data maintenance. Asset utilization metrics were built at the product-line level, including average cycle length and process time in hours and average idle time as a cycle-in percentage, giving leaders visibility they had not had before.
The work closed with a product-level implementation roadmap focused on defined targets, along with a blueprint for future master data maintenance and development. The cumulative effect was a scalable rhythm-wheel model that supported decision-making and planning, gave the plant far greater visibility into its operations, efficiency, and asset utilization, and replaced equipment-availability scheduling with a structured, defensible production schedule.
The Full Result
Two deliverables that gave the plant a true production schedule and a clear path toward its capacity target.
93%
Products Scheduled
The quarterly rhythm-wheel schedule covered 93% of products by volume at the primary Americas site, including the low-running products positioned to protect capacity for the high-running 'A' products.
5 weeks
Time to Deliver
The rhythm-wheel model, demand simulations, standard work, asset utilization metrics, and implementation roadmap were all developed and delivered within five weeks.
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At one of the industry's most complex sites, POWERS built a quarterly rhythm-wheel schedule covering 93% of products by volume in five weeks, turning a plant that scheduled work on equipment availability alone into one that finally knew its true capacity.
Global Specialty Pharmaceutical Manufacturer
Executive Brief
The plant scheduled and ran work on a 7-day cycle based on equipment availability alone, with cycle-time expectations unknown, cleaning operations disconnected from the schedule, and ERP standards that did not match what production personnel reported, leaving true capacity an open question against a goal of 30% higher throughput on existing technology. POWERS applied an Integrated Management System approach, taking a floor-level look to find the gaps and then tying them back to the existing information systems, and designed a 90-day rhythm-wheel production schedule supported by demand simulations, standard work, asset utilization metrics, and a product-level implementation roadmap. The quarterly schedule accounted for 93% of products by volume at the primary Americas site, and the full model was delivered in five weeks.
Results at a Glance
93%
Products Scheduled
5 weeks
Time to Deliver
The Situation
A plant that ran one of the industry's most complex product mixes on a 7-day cycle set by equipment availability, with no real read on its own capacity.
Beneath the goal sat a structural problem. Work was being scheduled and performed on a 7-day cycle based simply on equipment availability, with no defined standard work for machine setup and cleaning, and cleaning operations that were not linked to the production schedule at all. Cycle-time expectations were unknown or uncommunicated on processes that ran as long as 96 hours, and there was no process to compare elapsed against appropriate cycle times. Compounding all of it, multiple IT data platforms generated reports that did not necessarily reflect what was happening on the floor, and the standards in the ERP system did not match what production personnel reported. True capacity was effectively unknown.
Leadership needed to determine the plant’s actual capacity, develop an optimal rhythm-wheel schedule, and link those disparate systems back to supervisory behavior, skills, communication, and decision-making. This was not a one-time fix. It required a structured production schedule built on correct standards, operating procedures, and behaviors, along with a defensible answer to whether the operation could absorb 30% more volume at all.
The Diagnosis
Six structural gaps producing the same outcome from six directions.
Scheduling driven by equipment availability alone
Work was scheduled and performed on a 7-day cycle based simply on what equipment was free, with no structured production schedule. Without a planned rhythm, sequencing was reactive and there was no foundation for raising throughput predictably.
Cleaning disconnected from the schedule, no standard work for setup
There was no defined standard work for machine setup and cleaning, and cleaning operations were not linked to the production schedule. Time-consuming changeovers and cleanings happened outside any plan, eroding available capacity in ways no one could account for.
Cycle times unknown and never checked
Cycle-time expectations were unknown or uncommunicated, and there was no process to compare elapsed against appropriate cycle times, on processes running as long as 96 hours. Long runs could drift well past expectation with nothing flagging the loss.
ERP standards that did not match the floor
The standards used in the ERP system did not match what production personnel actually reported. Planning and master data were built on numbers the operation itself did not recognize, undermining every downstream schedule.
Inconsistent data hiding true capacity
Multiple IT platforms generated reports that did not reflect what was happening on the plant floor, and data was inconsistent across systems. With no reliable single picture, the plant's true capacity remained unknown.
No confidence the plant could absorb 30% more volume
It was genuinely uncertain whether operations could accommodate 30% higher volumes across 76 product families, 80% of them extended release, at one of the industry's most complex sites. Leadership had a target but no validated basis to commit to it.
What POWERS Did
Designed a quarterly rhythm-wheel schedule and made the plant's true capacity visible.
POWERS used an Integrated Management System approach, taking a floor-level look to identify the gaps and then tying them back to the existing information systems. The scope was to develop a 90-day rhythm-wheel production schedule that could be replicated at other high-velocity plants. POWERS modeled actual production equipment capacity against the demand timeline using the rhythm wheel, supporting an Infor Advanced Planning and Scheduling implementation, and ran simulations based on average weekly demand to validate that the schedule supported market requirements.
In parallel, the team established inventory requirements for low-running products so they would protect capacity for the high-running ‘A’ products, freeing capacity in the process, and defined optimal product inventory levels to sustain high customer service. POWERS created standard work sequences for all products at all stages, including setup procedures, run parameters, and cleaning specifications, and developed the standard operating procedures and required behaviors for future master data maintenance. Asset utilization metrics were built at the product-line level, including average cycle length and process time in hours and average idle time as a cycle-in percentage, giving leaders visibility they had not had before.
The work closed with a product-level implementation roadmap focused on defined targets, along with a blueprint for future master data maintenance and development. The cumulative effect was a scalable rhythm-wheel model that supported decision-making and planning, gave the plant far greater visibility into its operations, efficiency, and asset utilization, and replaced equipment-availability scheduling with a structured, defensible production schedule.
The Full Result
93%
Products Scheduled
The quarterly rhythm-wheel schedule covered 93% of products by volume at the primary Americas site, including the low-running products positioned to protect capacity for the high-running 'A' products.
5 weeks
Time to Deliver
The rhythm-wheel model, demand simulations, standard work, asset utilization metrics, and implementation roadmap were all developed and delivered within five weeks.
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