Humanizing the plant’s machines

Cognitive engineering combines contextual awareness and situational intelligence.

10/18/2017


The human versus machine debate has been going on for entire careers, especially for those who have spent a lifetime building machines, programming them, feeding them with data, and then directing them to provide the needed results.Photo by Alex Knight on Unsplash

Machines can be stronger and faster than humans, without tiring or experiencing emotional difficulties and other distractions. Human differentiation derives from a keen sense of perception, the ability to look at things from numerous angles and make objective, informed decisions.

The human mind perceives and reacts to situations by combining knowledge (acquired through past experiences and learning) with a contextual understanding and situational awareness of things.

The growth of technologies that help machines sense, analyze, and learn better, as well as contextualize, has given rise to the field of cognitive engineering. At its core, cognition is about humanizing machines.

Combined cognition

Three areas of focus can move cognitive systems from where they are to a more advanced and useful future.  

1. Interactions must shift from pushing a button or opening an app to gesturing, using sign language, expressions, or the voicing of emotions. At a fundamental level this requires advanced voice and image processing tools. Reinforcement learning algorithms under development will equip cognitive systems, over time, to identify and respond to various gestures and emotions. The challenge is to accurately engineer models, not just cognitive systems, but the entire world around them.

Imagine a home automation system that analyzes human expressions to select a desired music track or adjusts a thermostat by assessing human body movements.

Collaborative robotics (“cobotics”) in production plants can perform tasks just like another shop-floor co-worker, with greater precision and perhaps more quickly. Robots equipped with advanced machine vision nearly can eliminate errors and quality control issues on the production line.

2. Decision-making needs to be quick, bias-free, based on evidence, and backed by strong reasoning algorithms. In an industrial manufacturing plant, sensors collect huge amounts of data at every stage of the production line. Most data effectively used.

The focus must shift from building analytical capabilities on the cloud to edge-empowering businesses with access to real-time insights. Fault-model libraries under development can speed-up learning and fast-track reinforcement in cognitive systems. These libraries analyze and study patterns of various plant processes and machinery over an extended period of time. The consolidated learning is then fed to cognitive systems to give them a massive head-start.

Cognitive systems trained this way autonomously can optimize processes to lower costs or speed up production. Artificial intelligence (AI) may be used for monitoring sustainable governing practices in manufacturing plants.

3. Standards must be open. With so many companies developing AI and machine learning tools, the creation of industry standards will be a huge boost to the cognition world. Standards will go beyond just bringing in more developers to the ecosystem and enable businesses to invest in a standardized set of tools to build machine intelligence.

This technology revolution is being critically molded by the technical decisions we are making now. Evolving human and machine interactions, training cognitive systems, and developing industry standards can evolve cognitive systems further.

Bhupendra Bhate is chief digital officer, L&T Technology Services Ltd., a CFE Media content partner.



The Top Plant program honors outstanding manufacturing facilities in North America. View the 2015 Top Plant.
The Product of the Year program recognizes products newly released in the manufacturing industries.
Each year, a panel of Control Engineering and Plant Engineering editors and industry expert judges select the System Integrator of the Year Award winners in three categories.
Pipe fabrication and IIoT; 2017 Product of the Year finalists
The future of electrical safety; Four keys to RPM success; Picking the right weld fume option
A new approach to the Skills Gap; Community colleges may hold the key for manufacturing; 2017 Engineering Leaders Under 40
Control room technology innovation; Practical approaches to corrosion protection; Pipeline regulator revises quality programs
The cloud, mobility, and remote operations; SCADA and contextual mobility; Custom UPS empowering a secure pipeline
Infrastructure for natural gas expansion; Artificial lift methods; Disruptive technology and fugitive gas emissions
Power system design for high-performance buildings; mitigating arc flash hazards
VFDs improving motion control applications; Powering automation and IIoT wirelessly; Connecting the dots
Natural gas engines; New applications for fuel cells; Large engines become more efficient; Extending boiler life

Annual Salary Survey

Before the calendar turned, 2016 already had the makings of a pivotal year for manufacturing, and for the world.

There were the big events for the year, including the United States as Partner Country at Hannover Messe in April and the 2016 International Manufacturing Technology Show in Chicago in September. There's also the matter of the U.S. presidential elections in November, which promise to shape policy in manufacturing for years to come.

But the year started with global economic turmoil, as a slowdown in Chinese manufacturing triggered a worldwide stock hiccup that sent values plummeting. The continued plunge in world oil prices has resulted in a slowdown in exploration and, by extension, the manufacture of exploration equipment.

Read more: 2015 Salary Survey

Maintenance and reliability tips and best practices from the maintenance and reliability coaches at Allied Reliability Group.
The One Voice for Manufacturing blog reports on federal public policy issues impacting the manufacturing sector. One Voice is a joint effort by the National Tooling and Machining...
The Society for Maintenance and Reliability Professionals an organization devoted...
Join this ongoing discussion of machine guarding topics, including solutions assessments, regulatory compliance, gap analysis...
IMS Research, recently acquired by IHS Inc., is a leading independent supplier of market research and consultancy to the global electronics industry.
Maintenance is not optional in manufacturing. It’s a profit center, driving productivity and uptime while reducing overall repair costs.
The Lachance on CMMS blog is about current maintenance topics. Blogger Paul Lachance is president and chief technology officer for Smartware Group.
The maintenance journey has been a long, slow trek for most manufacturers and has gone from preventive maintenance to predictive maintenance.
This digital report explains how plant engineers and subject matter experts (SME) need support for time series data and its many challenges.
This digital report will explore several aspects of how IIoT will transform manufacturing in the coming years.
Maintenance Manager; California Oils Corp.
Associate, Electrical Engineering; Wood Harbinger
Control Systems Engineer; Robert Bosch Corp.
This course focuses on climate analysis, appropriateness of cooling system selection, and combining cooling systems.
This course will help identify and reveal electrical hazards and identify the solutions to implementing and maintaining a safe work environment.
This course explains how maintaining power and communication systems through emergency power-generation systems is critical.
click me