By Jari Åberg, Elomatic
Automation in production and industrial environments can be interpreted as a multi-tiered structure where each level has its own specific tasks, characteristics and place. The highest level of information management concerns Enterprise Resource Planning (ERP) systems, under which there are Manufacturing Execution Systems (MES) and actual production process management systems, i.e. Distributed Control Systems (DCS). The entire structure can and should be built to be flexible so that it can be supplemented, if required, according to changing production requirements.
MES software and applications have been developed to supplement ERP systems and act in between ERP systems and process automation applications. For an automation system to operate optimally it is essential that data is able to flow smoothly and predictably from one system to another.
The development of MES-level structures for process automation was started more than 20 years ago. Since then standards have evolved and guided converging system structure architecture towards current models.
In practice, tasks are distributed in automation so that the ERP system acts at a business level in operational control, whereas MES takes care of plant-level production control. Traditional process automation focuses mainly on process and line control at a plant level. See Diagram 1.
Over the past 25 years automation has taken giant leaps of several generations forward in terms of technological development. Traditional process control systems have e.g. been furnished with MES-level functions that can be widely utilised in the design of software applications.
Diagram 1. Industrial automation systems are multi-tiered structures with each tier taking care of specific tasks. The system needs to be sufficiently flexible to allow for different production requirements and conditions. (Based on ISA-95 model)
Internet of Things shaking up automation
The operations of modern automation systems have been strongly affected by the Internet of Things (IoT), i.e. the Industrial Internet, which enables digital communications and data transfer between different devices, generating a system network between different systems. It can be said the IoT has already boosted the management of different kinds of plant data, and will increasingly do so in the future.
Process devices are becoming increasingly smart and produce ever growing amounts of data. This data is transferred via the IoT and used in conjunction with business operations data for further analysis. Correctly and systematically collected data enables the efficient utilisation of the industrial Internet in boosting business operations.
When building an automation system, it is important to understand what kind of production technology the end customer uses at the production plant. Production and process control applications are often designed and configured for a specific end user or production plant, even though the application platforms, development software and systems used are standard packages.
Typically an application platform consists of a SQL database, an automation interface and a user interface base, on top of which all modules are installed. In the user interface base data processing can be illustrated visually using 3D modelling and/or panoramic images and applications can be seamlessly integrated with production automation. Users can view vital production information in a readable format on control room workstations, on the office wall or on various mobile devices.
The condition of production devices must be continuously monitored and regular and preventive maintenance needs to be conducted. Plant maintenance, OEE (Overall Equipment Effectiveness) and condition monitoring are all included in a typical MES software package. Ultimately, the applications included depend on the end user and the business field. Medical applications, for example, require specific precision, thorough planning and management of the entire chain of operations; Good Automated Manufacturing Practice (GAMP).
Data storage, refining and security increasingly important
In recent years the effective storage of vast amounts of data has become a key requirement. Data pertaining to product information, for example, is particularly valuable and supports product safety and the reliable traceability of products. The overriding objective is that the system and any data therein produces benefits for business operations, improves production efficiency and allows operators to react more quickly to changes.
As the industrial Internet fast becomes commonplace the importance of information security in automation systems and their connection networks has been highlighted. Cybersecurity has received much public attention. It is a challenge in industrial networks and cannot be ignored. The industrial Internet is connected to the outside world, which necessitates the use of firewalls, bridges and information security software to prevent the system from harm.
Typical security risks include external malicious actions aimed at systems and data theft. System owners and users naturally also need to be disciplined and follow any instructions provided.
The public Internet and office networks are already infested with different kinds of computer viruses and malware and these bugs can also find their way to the Industrial Internet – either by accident or through intent.
The increase in the volume of data collected by systems and the number of devices connected is placing growing demands on the entire system, which emphasizes the need for data re- fining. Despite the challenges posed by the sheer volume of data, we still need to be able to find the right piece of information at the right time, every time.