Strategic Automation for Process Industries
Published on : Wednesday 15-07-2020
Lack of availability of skilled resources, rapid developments in technology, and ever-demanding customer needs are shaping the future of automation, says Vignesh Kumararaja.
Automation in manufacturing has been acknowledged as a competitive differentiator in the past couple of decades. With the advent of Industry 4.0 and IIoT-enabled workplaces, it will be a necessity. The appropriate level of automation for a plant has been debated over numerous proposals. Frost & Sullivan's study on ‘Impact Assessment of Automation in the Indian Manufacturing sector’ estimates that the global automation market is set to witness growth as investment in automation is expected to increase. It indicates that the industry is moving toward automation to improve quality and efficiency. While there are no hard and fast rules to determine the appropriate level of automation, the needs of each manufacturing unit vary from each other and even over time. There are a few guiding principles that can help with the implementation of automation.
ISA-95 can serve as a Reference Point
ISA-95 is a standard developed by the International Society of Automation. This standard provides a technology-agnostic model for the automated interface between manufacturing control functions and enterprise business functions. The model has continuously evolved over the past two decades to meet the needs of industries and enhances the adoption of principles toward Industry 4.0. The standard automation pyramid of ISA-95 (Exhibit 1) has four levels. Levels 0 to 2 are for process control. Level 3 is for MES (manufacturing execution system) and Level 4 is for ERP
(enterprise resource planning). Level 0 deals with data collection and ensuring the authenticity of data. The process variables, such as temperature, pressure, flow, etc., are captured with the help of sensors and controlled by actuators. Sensors and actuators are called field instruments and determine the accuracy of process control.
Level 1 is for consolidation and correlation of the data with the pre-defined logic. The selection of controllers (PLC & DCS) depends on the expected response time, scalability, redundancy, complexity, and changes. Level 2 is about decision support systems to enable process control. Monitoring, acquiring, and real-time processing of the data from field instruments through controllers help to directly control the process over and above the pre-defined control logics. Level 3 is all about integrating the control systems with MES to enable data-based decision making and real-time performance monitoring and enhance operational efficiency. Level 4 fulfils the core objective of the ISA-95, which integrates the MES with ERP for real- time visibility across the value chain.
Types of Automation
While discussing automation in manufacturing, it is imperative to note that the automation requirements of different industries vary, even with time and location. Classification of manufacturing industries into process type and discrete type enables us to set specific guidelines around automation requirements. As a rule of thumb, in all process industries, the equipment governs the capacity, quality, and productivity of the product. We can classify the scope of automation in process industries into process automation and information automation.
Process Automation
Modern technologies provide many automation solutions for the manufacturing process. But selecting the right one is based on the need and value addition to the business. Key factors listed here may help prioritise the automation requirements.
A. Safety
Safety is becoming a top consideration over the typical cost of investment-based decisions on automation. The priority is to automate the processes at Levels 0 and 1 that are potentially hazardous or fatal.
B. Quality
Implementation of advanced auto controls at Levels 0 and 1 for critical-to-process parameters results in improved process capability, yield, repeatability, etc. The nature of the process determines the level of automation.
C. Productivity
Especially in the process industry, data analytics provides insight into reducing processing time, reducing changeovers, optimising resources, etc. The selection of the right field systems at Levels 2 and 3 opens up many avenues for improvement in productivity.
D. Cost
Traditional RoI (return on investment) calculations are giving way to elements like business continuity and risk mitigation for automation investments.
Information Automation
Data is crude; however, if refined, we obtain the ideal fuel to kick-start the growth engine. Automation of data gathering and analytics will help in the precise identification of improvement opportunities in the areas of supply chain management, production management, asset reliability, and quality.
A. MES & ERP Interface
An MES & ERP interface connects the entire value chain in a common link for better visibility. Tools such as an intelligent dashboard measure and monitor the real-time impact in the operation using diverse data. Data analytics and visualisation help the leadership team have absolute control and command over the enterprise.
B. Big Data Analytics
Big Data analytics facilitates the shift from logical guesses to empirical decision-making. Accurate and reliable information with high velocity, volume, and mix is necessary for a good analytical decision. The enhanced data requirement of Big Data analytics tools demands IoT (Internet of Things)-enabled devices in the field. For instance, Big Data analytics can predict the demand and supply risks and eliminate chronic defects.
C. Machine Learning, Deep Learning and Artificial Intelligence (AI)
Manufacturing companies, especially in many process industries, are successfully using machine-learning algorithms to improve their process. Machine learning helps in prescriptive/predictive maintenance to avoid breakdowns. Deep learning automates the complex planning process and simulates various safety scenarios for risk analysis, and AI plays a vital role in replacing the human potential and skill assessment.
Time for Strategy
Lack of availability of skilled resources, rapid developments in technology, and ever-demanding customer needs are shaping the future of automation and the changing landscape of industry dynamics. Factory automation has morphed from being evaluated on RoI based on cost-savings to being on the CEO's list of important things to evaluate to be future-ready. Appropriate maturity in deployment and alignment of automation systems at different levels in the organisation will improve the overall efficiency and give a competitive advantage. When the routine is disrupted, such as now, we must take a more holistic look at automation and its benefits.
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Vignesh Kumararaja is Consultant, Manufacturing & Process Consulting Practice, Frost & Sullivan. Vignesh is business excellence professional with 10 years of experience in Operational Excellence, Manufacturing Operations, Quality Function, SCM Integration, Innovation & Technology Management. He is proficient in assessing the maturity of the manufacturing facilities on a global scale and supports teams on complex project execution – using tools, initiating change, and applying sound improvement methodology.
