Overview

 

IIOT is a disruptive innovation in the industrial arena and its transforming manufacturing conventions. It works with factual data and logics to produce tangible outcomes in productivity, process and people management. It has no room for assumptions or human/manual errors as it does machine to machine communication(M2M) in real time. Real challenge is how to analyze and channelize big data for cognitive tasks and resource efficiency.

Machinery Intellectualization

Rigorous start

It starts with defining data outcomes from each and every asset with cognitive conditions, scenario to scenario, and task to task. It requires the enhancement of machinery,   which can be achieved by adding sensors and custom embedded chips to produce data. One point to address in this report is that  cost of sensors are very low as compared to stopping production or postponing the adding sensors to machines. Process of smart implementation is fundamentally complex, but not impossible. There are various ways of doing maintenance and switching production in general.

Capturing and Communicating Data

Capturing

Automated data capturing in real time create visibility to understand production, process, risk, asset conditions and so forth. It also means that it reduces turnaround time, human efforts and assumption from manual/digitally filled data-sheets by human. Machines capture massive amount of data.  It is very important that we learn to dispose of  (losing) unnecessary data, grouping and categorizing of useful data, as well as (and also) having  the appropriate mechanisms to capture meaningful data touch points. Forward data which is useful and help making decision faster.

Communication

Machine to machine communication (M2M) is a great  benefit for cognitive automation and machine learning. Machine learning helps one  understand patterns, errors, failures and capacity. This is the time where we need software to store, analyze and collaborate with data.

Predictive Analytics

Combination of static data touch points and real time produced data, becomes just “Big Data”. Smart and meaningful software can early predict impact, cause, attrition , safeguards and proportional value  recommendations. That changes the analysis approach altogether, from reactive to proactive by a  minimum cross check and customization,  allowing enterprise to take powerful calls to action for upcoming causes. This makes enterprise super efficient and accurate to lead at profitability.

Human Empowerment

Knowing the solution is half of the victory  until it is not implemented. Implementation is the most difficult phase  where humans have to perform various tasks.   It is all about calculating the   ability, degree of autonomy, and estimating the overall accountability. It is entry point to have “Internet of Everything (IoE)” where people, process, data and things are collaborating with one another . Not just to plan efficient operations, but to empower humans in the field, to increase the degree of self-determination for necessity helps in various medium/multimedia with operational history to futuristic advancement advices.

Security Challenges

It has two big changes where one is IT infrastructure and data-bank,  and the second is physical assets/machinery and their controlling systems. In any industry the majority of the machines have been installed 10/20/30 years ago, therefore  security standards are not as advanced  as they should be,   on other hand new machinery is not 100% safe from hacking attacks. We can do our best to be protected from hacking attacks, but to do so we have to continuously detect and set new updated protocols for predictive threats.

Solution could be…

Start with a long-term vision even if you are nowhere near beginning and/or breakdown into achievable milestones. It allows you to think of maximum number of possibilities and create complete robotic/automated solution.

  1. Aim for building fewer but smarter interfaces that require minimal or no human intervention.
  2. Present the most effective and useful  data with minimalistic navigation system.
  3. Drive with notification, provide the best possible solution with further actionable items, to make it proactive, suggestive and reliable.
  4. Defining strong use-case scenarios to deal with current and futuristic technology/devices.
  5. Make it valuable and beneficial for user, organization, environment, government and safer even for those people who are not part of the business.

Samples:

 

Home Page: Start simple with priority. Empower user by providing data as per schedules. Think of intelligent and  collaborative solutions.

Make primary navigation to the point and the way human thinks.

FOCUSED HOME PAGE (Try to make it no brainer)

Detail Page: One hero action with all the needed details to help decision making, customization or quick/obvious verification.

Detail Page

Secondary Navigation: Make it scalable and guileful from user patterns and history.

BE LIKE A WATER MY FRIEND! — Bruce Lee

Image Courtesy: bilfinger.com, industryweek.com, opus-internet.fr, free stock photos.
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