What is Industrial Automation?

Industrial automation in its various forms has been around for more than half a decade.  However, its momentum in the past decade in terms of practical application is far more comprehensive and impactful than it has been in the past. So much so that everybody from policymakers to industry regulators are racing to ensure that it has the best possible impact for all stakeholders. Before delving further into the futuristic implications of industrial automation, let us first understand what industrial automation is.

After mechanization in the first industrial revolution and assembly lines in the second industrial revolution, manufacturing had achieved abilities to scale and grow. But post world-war, booms in economies worldwide backed by the boom in population ensured consumption remained ahead of production in developed economies. So, businesses and technology providers leveraged the power of sensors and actuators to build control systems that reduced the burden on human resources. The combination of process, sensors and actuators running on an integrated control system marked the advent of modern industrial automation.

The essential components of industrial automation fall under five broad levels aligning to the ISA 95 architecture:

– Level 0: Intelligent systems containing embedded electronics and data-gathering sensors.

– Level 1: Local control systems like relays, PLCs, etc.

– Level 2: Centralized control and data acquisition systems like SCADA. The aforementioned levels used in the manufacturing process converts raw material to finished goods.

– Level 3: Organizational and inter-plant processes that enable and guide the functioning of all the lower levels, while also providing an interface to the next level; such as Manufacturing Execution Systems (MES). 

– Level 4: Enterprise-level systems and applications that align manufacturing lines to business processes such as ERP, MRP or CRM systems.

These levels are defined by the ISA 95 framework (also known as IEC 62264) and determine the protocols for communication between different levels and control systems in the manufacturing environment. This allows communication between disparate systems and enables the tracking and analyzing of information to establish the interdependence of seemingly disconnected elements of a manufacturing enterprise.

Why Is Industrial Automation Used? The Benefits

It’s interesting to note that although the need for industrial automation emerged from the lack of necessary manpower, its benefits extend far beyond the scope of just manpower and staffing. Industrial automation reduces the errors and inefficiencies that result from manual processes and provides benefits including:  

– Increased productivity.

– Reduced production cost.

– Heightened quality assurance.

– Increased safety of the worker.

Increased Productivity

Automated manufacturing processes reduce the workload for factory floor teams. This allows them to focus on overall effectiveness and quality goals, which increase the value that each stage of the process contributes to the overall manufacturing environment. By creating more bandwidth for labor, appropriate investments in line capacity can also increase throughput and yield per square feet making manufacturing more and more profitable.

Reduced Production Cost

Human fatigue not only causes a dip in production but can also result in quality failures due to inattention. If a factory floor worker enters an incorrect temperature setting, for example, a piece of conduit can become too narrow. Deviations in product specifications along with the variability of output can increase scrap rates which adds to the overall cost per unit of the finished goods.

Heightened Quality Assurance

Errors in manufacturing can also result from circumstances like a lack of diligence or distractions. Whatever the reason may be, these errors cause inefficiencies and waste that may or may not be caught with testing and quality assurance infrastructure. Besides resulting in financial consequences like rejects and change requests, poor quality can also affect customer satisfaction and company reputation which could be detrimental to business.

Increased Safety of Workers

Hazardous environments make the use of automation inevitable. Processes that involve excessive heat, biohazards, heavy material or excessive noise, need automation to not only ensure production but more importantly to ensure safety of workers. Automation reduces the risk of injury at operational levels by removing factory personnel from dangerous work procedures.  Automated systems also tend to respond faster to emergencies by providing real-time monitoring. 

 

 

And, If It’s Smart Automation Technology, Perfect Production

Perfection of manufacturing process is impossible to do without the combination of process intelligence that throws light on both efficiencies and inefficiencies in specific areas of the process, and the ability to predict and suggest the ideal path for material flow for the most efficient and effective manufacturing. For example, Oden’s Golden Run, a proprietary machine learning algorithm can help manufacturers identify the most profitable way to create their products. 

What Are The Essential Constituents Of A Typical Automation In Manufacturing?

Earlier in this piece we saw at a high level the components of industrial automation by each level of the ISA 95 architecture. Now let us look at each of them and their relevance in more detail.

Programmable Logic Controller (PLC)

After relays and switches, PLCs are the most prominently used controller for both process control and machine control. They are very application specific and are programmed for a singular purpose. They are made to industrial specifications and can operate in tough conditions. 

Microcontrollers are used for a similar purpose, but the selection of PLC versus microcontrollers depends on the speed and precision required. Microcontrollers are smaller controllers with an onboard computer hence allowing more functionality for diverse applications while PLCs win in stability. Between both, they form the building blocks of what we will discuss later as Distributed Control Systems (DCS).

Human Machine Interface (HMI)

As the name suggests, this system allows Humans and Machines to interoperate. It allows humans to understand progress, operating parameters and sometimes even issues in a machine. It also allows the machine to receive commands and interventions from operators. 

Conventional HMIs were analog dials and knobs. But over time, the amount of information, its density and variety has demanded advances into digital displays allowing for intuitive interfaces like touch and gesture.

Since the primary use of this is to allow interface, it can exist at multiple levels like machine, field, plant and enterprise

Distributed Control System (DCS)

What PLC or microcontroller does at the level of a machine or a node, DCS does at the plant or facility level. It emulates the process of the entire plant and hence is aligned to and driven by the process. A DCS is applicable only if the control room is located locally in the same place as the plant. Historically, process plants where uptime and continuity along with safety are of paramount importance, DCS has found to be a good fit.                               

Supervisory Control & Data Acquisition (SCADA)

SCADA is a data acquisition and intelligence tool that provides insights into the performance of the manufacturing enterprise from a production and productivity standpoint. Information from SCADA can help in broader decision making and hence issue commands to respective plants. SCADA is different from DCS from the perspective that it is not process state driven but information or event driven. It goes without saying that different DCS systems can feed data to the central SCADA to harvest consolidated data over a large geographical area.

Artificial Neural Network (ANN)

With the advent of computers and their application in manufacturing, the ability to gather data and make sense out of it has become immense. However, it was all still analyzing past data and then human intelligence to take decisions. But with the developments in neural networks and machine learning, manufacturing systems can become quasi-intelligent. They can be trained to learn existing stimuli and response and asked to predict future outcomes through modeling. The models that enable these can not only predict outcomes but can also become intelligent enough to recommend actions to bridge the gap between “as-is” and “ideal” states.

AI does not eliminate the need for factory personnel in manufacturing, it empowers them in decision making by harnessing the power of intelligence and predictive algorithms.

Why Is Industrial Automation Needed? The Future Is 4.0.

Ever since a group of German industry intellectuals coined the word Industry 4.0, it has been making waves in the manufacturing space. The advancements in processing power of electronic systems, communication & data handling, big data, cloud computing and deep learning/ machine learning/ artificial intelligence have all come together to create a path for truly connected and intelligent Cyber Physical Systems (CPS).

For the first time ever the humongous volumes of data that are created in the entire manufacturing supply chain but have been lying unutilized, have started to create newer perspectives that were previously unheard of. For example, the upcoming return of a fleet of shipping trucks can be a treasure to a company that manufactures rotor blades for wind turbine installations and is racing against time to complete installations before fall. It will be the difference between profit and loss for a beverage manufacturer to know when and by how much the inventory needs to be stocked to meet the demands of a volatile market.

Outsmart The Competition

Agility in response to the demands of a dynamic market is no longer an edge over competition as almost all companies are embracing this philosophy in a volatile global marketplace. However, the key to perfecting that is through the power of a fully digital and automatic manufacturing environment that will empower the right decision makers and the operators with the required intelligence and recommendations. The businesses that embrace and realize the true potential of Industry 4.0 will enjoy sustained competitive edge as the technology and its application matures. 

Invest In Your Workforce

IIoT driven Industry 4.0 implementation along with the power of data visualization based on cutting edge decision support systems will define the way forward for operational excellence in manufacturing. Visibility of intelligence and impact from the shop floor to the top floor, will ensure a lock-step march towards business objectives and even more powerfully, towards the company’s “Golden Run” delivering maximum possible profitability.

Collect Incredible Data

Modeling the manufacturing business, not just the plant into a digital twin allows simulation of stimuli and outcomes enabling decision makers at all levels to benefit from the power to project, predict and prevent. This reduces uncertainties and hence the inherent risks can be mitigated or eliminated depending on the influencing parameters.

Hence Industry 4.0 not only increases production and profitability, but also contributes towards risk mitigation.

Produce At Full Efficiency, Every Manufacturers Dream

Thus, by combining all the benefits of artificial intelligence, machine learning, IIoT, mobile devices and cloud computing, Industry 4.0 helps everybody in the manufacturing enterprise to leverage data and analytics to make better decisions faster. 

Get Oden’s Help

Oden Technologies has demonstrated the power of AI and ML driven data visualization for manufacturers in a diverse set of industries spread across process or discrete product manufacturing.