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GSK

SUPPORTING THE BUSINESS CASE FOR A MAJOR FACTORY IN ITALY

CLIENT

GSK logo
REQUIREMENT
REQUIREMENT

GSK was planning to build a new sterile manufacturing facility, and needed a tool for the design optimisation and supporting the business case for this multi-million pound investment.

CHALLENGE
CHALLENGE

Capturing the complex processes required input from more than 30 experts. The expert knowledge informed the short time-frame development of a solution that is fast and accurate enough to explore the problem space and optimise solutions for different scenarios.

SOLUTION
SOLUTION

A dynamic AnyLogic simulation model that provides meaningful insights into the future production line. It allows optimisation of equipment, personnel and utility resources to meet the commercial demand forecast for the next decade.

Proving value
Proving value

GSK was planning to build a new sterile manufacturing facility in Italy. Its Front-End Engineering & Design (FEED) team had to develop the design concept to support the business case. A key project requirement was to establish the optimal level of resource (equipment, personnel, utility) to satisfy a decade of commercial demand forecasts.

Comprehensive, fast and flexible
Comprehensive, fast and flexible

Product forecasting and demand fluctuations have always represented a big challenge for companies especially during the design of a new manufacturing line or plant. Getting the right product mix, coordination and optimisation of resources such as machines, operators, materials, etc. are some of the challenges that GSK face operationally. For us the challenge, was developing a model that captured all the required complexity while being fast enough and flexible enough to answer the business questions and allow a wide exploration and optimisation of the problem space.

Simulating the future production line
Simulating the future production line

GSK addressed their planning needs by utilising simulation modelling for the new bio-pharma sterile product line. This approach created a highly accurate digital twin of the future production process.

The simulation model functioned as a testing ground for GSK. They could explore various what-if scenarios to understand the impact on production capacity and operating costs.

This powerful tool provided specific answers to critical questions:

  • Machine quantity: The optimal number of machines needed for the line.
  • Machine technology: The most suitable technology for the chosen machines.
  • Operational setup: The ideal staffing levels, batching patterns, and other operational factors.

By leveraging simulation modeling, GSK gained valuable insights before committing to physical infrastructure and equipment.

Team effort
Team effort

We worked closely with GSK technical experts to develop the model, in a highly collaborative and successful relationship. It was a cross-functional learning exercise involving numerous GSK contributors across several counties and disciplines. This approach helped the design and production teams gain a holistic view of the capacity and operating as we uncovered the process logic and operational metrics. It also offered a high level of engagement within GSK, aided knowledge transfer and built confidence in the model and the insights it provides.

Foundation for the future
Foundation for the future

GSK are now entering the construction phase. We are proud that modelling has helped support this.

GSK's the top three benefits:

  • Faster approval timeline – the trust in the modelling outputs has smoothed the stage gate approval of the concept and allowed to move faster into the next project phase.
  • Increased confidence in the amount of equipment required for the new production line that ultimately led to reduction in CAPEX by a double digit number.
  • Ability to evaluate over 200 different business scenarios in a short amount of time.

Our tool has the capability to deliver continued value to the project so that in the future it will be possible to further evaluate capacity requirements as function of the demand forecast variability. The model also has the capability to be extended to people and material flow for the final operational layout.

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