OEE Improvements In Secondary Packing

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OEE Improvements In Secondary Packing

The secondary packing area was a site constraint and suffering from low OEE due to a number of factors.
OEE
OEE was low (<50%) due to long and inconsistent changeovers, poor planning, poor material flows, poor resource availability and poor layout. The goal was to improve the OEE by applying appropriate tools in all problem areas.
  • Rhythm planning was introduced to the packing area supported by simple modelling. The plan was fixed for the next 24hrs and was indicative after that
  • SMED techniques were used to improve standard changeovers
  • Material flows were improved components, products and change parts
  • Initial training was provided to packing operators and technicians and then they were involved in the improvement process
  • Closer management during packing orders was employed
Packing area OEE improved from 50 to 60%, quality improved, safety improved, work atmosphere improved, planning became calmer, the site got 20% more business due to improved reputation.
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Astra Zeneca – Product Release Lead Time Reductions

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Astra Zeneca – Product Release Lead Time Reductions

Final product release lead time was too long due to  quality and processing issues with documentation.

Astra_Zeneca

The batch documentation for a complex sterile product was very complex. The 
 ‘right first time’ (RFT) from documentation for final batch release was <10% and 
release lead-time after the final processing step was too long (4 days).
The goal was to dramatically improve RFT and to reduce the lead-time.

  • Documentation was simplified (remove unnecessary activity)
  • A Documentation Room (D Room) was created to allow documents to ‘flow’ through the process with errors being quickly corrected
  • Structure was added to documentation activities
  • Visual Management techniques were employed
  • Documents processed in sequence rather than ‘by preference’
  • Documentation RFT improved to >90%
  • Lead Time dramatically reduced (4 days to <1 day)
  • Documentation seen as core part of them process rather than a necessary evil
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ColorMatrix – Driving Effective Innovation and New Product Development

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ColorMatrix – Driving Effective Innovation and New Product Development

ColorMatrix is a leading global manufacturer of liquid color and additives for plastics. Rapidly growing the company success depends on the rapid design and launch of new products developments (NPD).
A highly innovative and customer focused culture had resulted in the launch of a large number of product development programmes.
Consequently technical resources were spread very thin, priorities were unclear, and NPD projects were not being delivered effectively.

Case-Study-ColorMatrix

ColorMatrix required:

  • Clearer development priorities driven from business and market needs
  • A more structured NPD process to ensure product development projects carried out efficiently and effectively without stifling the creativity and innovation that is central to company’s success

Design and implementation of market planning process to give strategic market direction to innovation and NPD.

  • Leadership workshop to select top 6 strategic NPD programmes
  • Designed Stage – Gate NPD process
  • Designed Tools, Templates, and Governance Process
  • Trained Leadership, NPD and Market Teams in Process
  • Trained R and D teams in DOE as a key product design and optimisation tool
  • Much clearer focus on ‘vital few’ development priorities
  • More rapid NPD and increased return on NPD investment
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Sanofi / Rexam – Medical Device Quality Improvement

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Sanofi / Rexam – Medical Device Quality Improvement

Data Analytics with JMP used to successfully tackle ‘rare event’ and complex quality problems with medical devices.

medical_device
Medical devices were produced in large batches on very high volume manufacturing lines. Batches were sampled using a destructive test. Occasionally very low levels of defects (ppm level) were detected. Complete batches of suspect product had to be scrapped. The goal was to better understand the problem and to improve yield and OTIF.
  • Rigorous statistical analysis of historic test data (over half a million tests!) to identify possible factors e.g. production lines, products, components and test machines.
  • Design of Experiments to identify root causes.
  • Changes to product design, manufacturing conditions, test machine calibration, sampling strategy.
Scrapped batches and major supply chain disruptions were reduced by a factor of 3. Major cost savings and customer confidence was greatly increased.
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Elanco – Poultry Case Study

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Elanco – Poultry Case Study

Extracting information from noisy data combined with advanced Data Analytics have helped Elanco deliver value added services in their animal health business.

Read more about our success with Elanco and JMP here

Microsoft Word - Case Study Elanco2.docx

Analyze data collected from more than 500,000 chickens and recommend health-enhancing practices to poultry producers.

Process Insight Consulting works with Elanco Animal Health veterinarians at “demystifying data analysis” using JMP® statistical discovery software from SAS.

Elanco veterinarians and technical consultants uncover statistically significant links between various genetic, dietary and environmental factors affecting the health and development of chickens, then communicate analysis results to producers in an easy-to-understand format.

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Macfarlan Smith – Improved Morphine Extraction

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Macfarlan Smith – Improved Morphine Extraction

Process Insight collected plant performance data and used JMP to analyse data sets bringing the process under control.

 

White papers

Big investment made but plant not delivering to target capacity. Critical business need to increase output but process chaotic – extremely difficult problem to solve!
But solution will deliver huge value to the business.

Collect plant performance data and use JMP to analyse data sets. Data was stored in lots of different systems which we brought together in JMP and discovered that morphine rate and solvent feed into the plant was not well controlled and morphine concentrations and solvent flow from the extractor was highly variable and off target,

By controlling the feeding rate and therefore morphine into the plant concentrations and flows are optimised to maximise output. Extraction capacity of morphine from poppies increased by 10%.

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