Aside from the wider pressures to reduce costs, the move towards smaller and more frequent drug launches adds to the opportunities for efficiency improvements at the manufacturing stage. Small gains here can contribute to considerable savings overall.
Pharmaceutical companies are examining the use of data in the manufacturing process, with smart factories expected to bring dramatic improvements.
A survey by Bain & Company found that pharma executives expect smart, connected factories to produce savings of 20% or more. They forecast a 17% reduction in costs related to inferior quality and a 15% decline in the cost of converting raw materials into drugs and a 14% increase in delivery reliability.
Some of these developments are relatively easier to implement and can deliver quick gains. Efficiency savings from these can be reinvested to help develop harder to implement and more advanced solutions in the future.
For the short term, therefore, pharmaceutical companies are looking at options such as:
Production Performance management:
Real time data from manufacturing equipment produces an overview of the entire production system.
Cloud based networking:
Companies of all kinds are moving to the cloud. Its enhanced capacity allows for big data management and can give managers an overview of data and processes from any location in the world. It also improves collaboration between multiple teams and helps improve coordination
A more effective analytical view of their global supply chain allows companies to optimise logistics and drive down costs.
Advanced analytics for predictive analytics:
Data from sensors identify breakdown patterns. This allows companies to predict the performance of parts and optimise maintenance. The early warning gives production teams a change to minimise downtime.
Advanced changeover support:
Movement of teams on the shop floor when reconfiguring machinery has an enormous impact on downtime. Technology such as video simulations or VR classes help operators follow a predefined procedure and accelerate the time taken for changes.
In the future they are working towards:
Predictive quality management planning:
Recognises patterns linked to quality problems which helps teams avoid defects and react faster and more effectively to problems. Identifying the root causes of problems helps teams address issues in a more timely manner.
Augmented and virtual reality machine maintenance:
Virtual reality and augmented reality are being used across the process. They can add to the real time information at the hands of staff and also help communicate data in real time.
Blockchain in supply chain for quality inspection:
The blockchain has a potentially transformative impact on how data is stored and transferred. It is immutable and allows for greater capacity in data handling.