Blog : by Earle Roberts, Foodmach CEO
Industry 4.0 supports better business decision making through the acquisition of real-time data into intelligent ERP (business management software).
The major challenges facing manufacturers as they introduce Industry 4.0 to their production lines are around budgets, internal expertise and older equipment or legacy systems.
Most established factories contain legacy machines of varying ages, PLCs and robots of one type or another.
Each older machine may have a different legacy protocol, making it difficult to connect them to an IoT solution that will mine their valuable data.
Legacy systems have not been designed or programmed to scale up, accommodate extra data points or to connect to the cloud.
The potential downsides of doing this are:
Adding cloud functionality to a system with no security for remote connectivity is an obvious security risk.
A user name and password with basic authentication may not be enough to prevent unwanted access.
Systems made for IoT integration will employ high-performance authentication, encryption and access rights management technologies.
Legacy machines were designed for one on one connection and communication with a PLC.
These outdated systems do not support the multiple data points required by modern IoT systems.
Although adding a data mining layer can enable them to report basic performance information, it probably won't help with predictive and ongoing maintenance reporting—which may need additional sensors—or scalability.
Legacy system interfaces tend to be hardcoded for reporting, usually via spreadsheets.
The facility for custom data acquisition cannot simply be added through access to the IoT, it needs to be programmed in.
4. REMOTE MANAGEMENT
One of our recent clients jokingly said he'd like to be able to remote monitor his company's entire new production line from an iPad while sitting on a houseboat.
While we supplied him with that capability (and more), it's an easier thing to deliver on all new production line.
It requires a level of access to data that a simple data mining over older equipment doesn't deliver.
Even a simple cloud protocol can involve upgrading the control systems on older equipment.
Requesting each OEM (Original Equipment Manufacturer) to upgrade equipment can be an expensive exercise.
Integration of old and new machines across a production line is usually the first step in any Industry 4.0 equation.
It requires an understanding of the varied legacy systems and protocols, the ability to 'break' them open, reprogramming of PLCs and connection to extract data and then deliver it to the cloud or an on-site system for further analysis.
Using high-level control architecture (OMAC, which stands for Open Modular Architecture Control) and open-source packaging machinery language (PackML), it is possible to work through OEM proprietary platforms and network them for access to useful, translatable data.
Interoperability is essential to capturing the full benefits of the Industry 4.0 revolution.
Put simply OMAC and PackML enable a modular approach for re-useable machine code, a standardised way of looking at operating modes, machine states and tag names on a packaging line from multiple OEMs using different control systems.
ISA 88, the process controls standard for two decades is the third standard providing a consistent terminology and framework for designing and modularising complex packaging systems. ISA 88 physical model provides a way of dividing the physical equipment into a hierarchical structure.
A good Line Management Execution System (LMES) will collect and deliver this data to supervisory control and data acquisition (SCADA) systems, manufacturing execution systems (MES) or enterprise resource planning (ERP) level systems.
Working with a team of specialists with proven Industry 4.0 expertise around legacy equipment will mitigate the costs and optimise the outcome.
As always, the right solution is customer-needs driven.
If you need some advice about updating your packaging line and introducing some Industry 4.0 connectivity,
Read more about applied Industry 4.0: