Improving pharmaceutical productivity

13 August 2018

Howard Forryan explains how predictive maintenance can help to reduce production line downtime in the pharmaceutical industry.

Postgraduate students from the Centre for Doctoral Training in Embedded Intelligence at Loughborough University were challenged by HARTING to investigate practical application solutions where MICA, its open industrial edge-computing platform could be applied to the benefit of UK manufacturing. Simple seamless integration within existing established production processes was the target, based on the concept of machine predictive maintenance.

The key objective was to achieve immediate productivity improvements and return on investment (ROI), to satisfy the trend for Industry 4.0 implementation on the factory floor.

The team looked at volume manufacturers in the pharmaceutical industry – in particular, companies manufacturing tablets using automated presses and punch tools.

Data from these machines can be collected using passive UHF RFID transponders which can be retrofitted to existing tablet press machines and mounted on the press-die/punch tools. The RFID read and write tags can record the pressing process – the number of operations performed by a particular press die – plus any other critical operating sensor-monitored conditions. The system can then review this data against expected normal end-of-life projected limits set for that die.

The data can be managed and processed through MICA, which can then automatically alert the machine operator when maintenance needs to take place to replace a particular die-set before it creates a tool failure condition and breakdown in the production line.

An open environment
MICA provides an open system software environment that allows developers from both the production and IT worlds to quickly implement and customise projects without the need for any special tools. Applications are executed in their own Linux-based containers, which contain all the necessary libraries and drivers. This means that package dependencies and incompatibilities are eliminated. In addition, such containers run in individual ‘sandboxes’ which isolate and secure different applications from one another with their own separate log-in and IP addresses. As a result, there should be no concerns over data security when MICA is allowed access to a higher-level production ERP network.

MICA is already offered with a number of containers such as Java, Python C/C++, OPC-UA, databases and web toolkits, all available on free download. As a result, users should be able to download links to the operating software system compatible with an existing machine, enabling full two-way communication with the MICA device.

Relaying such manufacturing information – which can comprise many gigabytes of data in the course of a day – directly to the ERP would normally overwhelm both the network and the ERP. With the MICA, however, this data stream is buffered directly onto the machine and can be reduced to just essential business-critical data using proven tools from the IT world.

The resultant productivity improvements can offer the following benefits:
• Less downtime reduces the amount of money lost during unforeseen maintenance of damaged punch tools.
• Individual punch identification will help in removing a specific punch, once it has reached its pre-set operational frequency working limit.
• A digital log of each punch and the number of tablets that it has produced is recorded. This provides vital information for Good Manufacturing Practice (GMP) regulators such as the Medicines & Healthcare products Regulatory Agency (MHRA) or the Food & Drug Administration (FDA).

Howard Forryan is a product market specialist at HARTING Ltd.

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