What is Process Automation ?
Process automation is the use of technology to automate processes to sequentially transition from one task to the next with minimal human intervention. It finds global application across functions and organizations. Given how rapidly customer demands are growing, it is critical to automate processes in order to stay relevant and profitable.
The importance of automation in the process industries increased dramatically in recent years in the industry 4.0. In the highly industrialized countries, process automation serves to enhance product quality, master the whole range of products, improve process safety and plant availability, efficiently utilize resources and lower emissions. In the rapidly developing countries, mass production is the main motivation for applying process automation. The greatest demand for process automation is in the chemical industry, power generating industry, and petrochemical industry; the fastest growing demand for hardware, standard software and services of process automation is in the pharmaceutical industry.
The traditional barriers between information, communication and automation technology are, in the operational context, gradually disappearing. The latest technologies, including wireless networks, fieldbus systems and asset management systems, boost the efficiency of process systems. New application fields like biotechnology and micro technology pose challenges for future theoretical work in the modeling, analysis and design of control systems, also the analysis of artificial agents. In this paper the industry trends that are shaping current automation requirements, as well as the future trends in process automation, are presented
What are the steps involved in Process Automation ?
If you’re considering process automation to enhance business operations, here are the typical steps to follow.
Understand historical data:
Start by identifying processes that need automation. Once you know what you wish to automate, you can delve into past performance. Seek to understand who are the stakeholders, what efficiency levels have been in the past, what are some common bottlenecks and errors encountered, what is the scope of improvement, and so on.
Define automation goals:
Once you have a solid understanding of the process, you are in a good position to begin defining goals for automation. In the absence of well-defined goals, process automation will lack direction and become a waste of time and resources.
Identify the right solution:
The right business process management solution is critical to automating processes. As the cliché goes, it can make or break the entire effort. Align your choices to your organization’s automation requirements.
Map out the process:
Process mapping or visual representation of the process is key to bringing clarity and transparency to the workflow. Every task, performer, and timeline needs to be included.
Incorporate needs of the team:
Tailor data to the end users’ requirements rather than bombarding them with irrelevant information. Identify key players and ensure that their automation needs are being address
Identify relevant key performance indicators (KPIs) to measure progress of processes. The chosen KPIs must be align to the goals defined in the beginning.
Test the automation:
Before rolling out the automation, test run it to check for loopholes and errors. Record small details that go awry and make the necessary changes.
Go live and monitor process:
Take the automation live. Customize your dashboard to monitor progress in real-time.
A key facilitator of process enhancement is documentation. Ensure that every single detail in the process automation exercise is recorded for future reference and analysis.
Conclusion of Process Automation
In large organizations in the bulk industries, the main emphasis in the future will be on the optimization of the assets. This optimization includes the initial capital, the operations and the distribution of the products. Process automation will clearly have a key role to play in this. In order to seek agility, the industry is moving towards various types of intermediate manufacture. The plants are smaller and tend to be closer to the customer. The key drivers to this are customization of size, quality, service and effect. The aim is agile systems which have the economics of a large single stream organization and the flexibility of a batch plant which, within limits, is able to make almost any product required. The dependence on process control will increase.
Design of very large distributed systems has presented a new challenge to control theory. A key issue in control engineering is the application to highly complex systems: the coupling of complicated and large heterogeneous systems in which different disciplines are involve and different types of information are available or have to be uncovered. New modeling methods are reported to be required which should provide a framework in which a priori knowledge of the process can be combine with existing modeling techniques.
You may also know Analysis of Intelligent agent in Artificial Intelligence