Software AG Case Studies Advanced Analytics for the Factory of the Future: A Case Study on Ashland Manufacturing

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	Advanced Analytics for the Factory of the Future: A Case Study on Ashland Manufacturing Software AG

Advanced Analytics for the Factory of the Future: A Case Study on Ashland Manufacturing

Software AG

Technology Category	Analytics & Modeling - Real Time Analytics Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries	Cement Pharmaceuticals
Applicable Functions	Quality Assurance
Use Cases	Additive Manufacturing Manufacturing Process Simulation
Services	Testing & Certification
Challenge	Ashland Manufacturing, a $5 billion US-based provider of specialty chemical solutions, was facing a series of challenges. The company was shifting its focus from construction materials to pharmaceuticals, a transition that brought about new challenges. This shift required higher added value, lower product throughput, and more control over production processes. The company was also dealing with seemingly 'unsolvable' production issues and a need for operational efficiency to boost quality and profitability. There was also pressure to increase Good Manufacturing Practice (GMP) production throughput. Furthermore, the company had to navigate the new territory of strict GMP standards relating to pharmaceutical product quality. Read More
About Customer	Ashland Manufacturing is a $5 billion US-based provider of specialty chemical solutions. The company employs 7,000 people worldwide and consists of two commercial units: performance materials and specialty (pharmaceutical) ingredients. The company has been manufacturing construction materials since the seventies and has slowly shifted its product focus towards personal care and pharmaceuticals. This transition has sparked fresh challenges for Ashland, requiring a shift towards achieving higher added value, lower product throughput, and more control over its production processes. The company's plant in Doel, Belgium handles the specialty ingredients. Read More
Solution	To address these challenges, Ashland turned to TrendMiner’s self-service industrial analytics solution. This platform provided actionable insights from processing data, analyzed automated plant production data in near real-time, and visualized this data for the team to apply proven methodologies such as Six Sigma and the DMAIC cycle. The platform was easily integrated with existing AspenTech IP.21 historian software, allowing product engineers to use it with familiar tooling like computer aided engineering (CAE) and advanced analytics without needing a data scientist. TrendMiner helped engineers discover which factors in the process were influencing the quality of the finished product and enabled process and production engineers to raise certain 'red flags' and prevent incidents from happening in the future. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Real Time Analytics

Platform as a Service (PaaS) - Application Development Platforms

Applicable Industries

Cement

Pharmaceuticals

Applicable Functions

Quality Assurance

Use Cases

Additive Manufacturing

Manufacturing Process Simulation

Services

Testing & Certification

Challenge

Ashland Manufacturing, a $5 billion US-based provider of specialty chemical solutions, was facing a series of challenges. The company was shifting its focus from construction materials to pharmaceuticals, a transition that brought about new challenges. This shift required higher added value, lower product throughput, and more control over production processes. The company was also dealing with seemingly 'unsolvable' production issues and a need for operational efficiency to boost quality and profitability. There was also pressure to increase Good Manufacturing Practice (GMP) production throughput. Furthermore, the company had to navigate the new territory of strict GMP standards relating to pharmaceutical product quality.

About Customer

Ashland Manufacturing is a $5 billion US-based provider of specialty chemical solutions. The company employs 7,000 people worldwide and consists of two commercial units: performance materials and specialty (pharmaceutical) ingredients. The company has been manufacturing construction materials since the seventies and has slowly shifted its product focus towards personal care and pharmaceuticals. This transition has sparked fresh challenges for Ashland, requiring a shift towards achieving higher added value, lower product throughput, and more control over its production processes. The company's plant in Doel, Belgium handles the specialty ingredients.

Solution

To address these challenges, Ashland turned to TrendMiner’s self-service industrial analytics solution. This platform provided actionable insights from processing data, analyzed automated plant production data in near real-time, and visualized this data for the team to apply proven methodologies such as Six Sigma and the DMAIC cycle. The platform was easily integrated with existing AspenTech IP.21 historian software, allowing product engineers to use it with familiar tooling like computer aided engineering (CAE) and advanced analytics without needing a data scientist. TrendMiner helped engineers discover which factors in the process were influencing the quality of the finished product and enabled process and production engineers to raise certain 'red flags' and prevent incidents from happening in the future.

Impact #1	The implementation of TrendMiner’s self-service industrial analytics solution has significantly boosted operational efficiency, compliance, and quality control across Ashland's plant. The platform has helped the company solve previously 'unsolvable' production issues and increase GMP production throughput. The use of TrendMiner's analytics platform has also enabled the company to stabilize production by identifying influence factors at the beginning of the process. Furthermore, the platform's monitoring capabilities have allowed engineers to prevent incidents from happening in the future. As a result, Ashland plans to continue moving forward with self-service industrial analytics, focusing more on real-time monitoring and real-time prediction of asset performance.

Impact #1

The implementation of TrendMiner’s self-service industrial analytics solution has significantly boosted operational efficiency, compliance, and quality control across Ashland's plant. The platform has helped the company solve previously 'unsolvable' production issues and increase GMP production throughput. The use of TrendMiner's analytics platform has also enabled the company to stabilize production by identifying influence factors at the beginning of the process. Furthermore, the platform's monitoring capabilities have allowed engineers to prevent incidents from happening in the future. As a result, Ashland plans to continue moving forward with self-service industrial analytics, focusing more on real-time monitoring and real-time prediction of asset performance.

Benefit #1	On-target production of GMP products increased from 70% to 95%
Benefit #2	Fast root cause analyses on complex data sets
Benefit #3	Improved quality control and compliance

Benefit #1

On-target production of GMP products increased from 70% to 95%

Benefit #2

Fast root cause analyses on complex data sets

Benefit #3

Improved quality control and compliance

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Overview

Advanced Analytics for the Factory of the Future: A Case Study on Ashland Manufacturing

Operational Impact

Quantitative Benefit