Accelerating the Industrial Internet of Things
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Use Cases Manufacturing System Automation

Manufacturing System Automation

An automated manufacturing system is the total integration of software and machinery used to create a system that performs manufacturing processes autonomously through computer programming.

Without automated manufacturing systems, factory output would be vastly reduced, production would be very time consuming, working conditions would be less safe and quality control would be extremely difficult. Employees would need to work twice as hard to achieve in a day what they can now achieve in an hour with automated industrial systems.

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Covisint Improves Mitsubishi's Collaboration With Its Supply Chain
Covisint Improves Mitsubishi's Collaboration With Its Supply Chain
Mitsubishi sought to improve supplier relationships on a global basis and to offer an easy-to-use solution to interact with them. In August 2004, Mitsubishi selected Covisint’s platform to help improve sharing of information and collaborative business processes with its global suppliers. Covisint enabled Mitsubishi to provide its suppliers with immediate access to information and applications to obtain more collaborative working relationships
Oracle's ML (Machine Learning) Applied Toward Big Data Processing
Oracle's ML (Machine Learning) Applied Toward Big Data Processing
Cloud, competition, big data analytics and next-generation “predictive” applications are driving companies towards achieving new goals of delivering improved “actionable insights” and better outcomes. Traditional BI & Analytics approaches don’t deliver these detailed predictive insights and simply can’t satisfy the emerging customer expectations in this new world order created by big data and the cloud.Unfortunately, with big data, as the data grows and expands in the three V’s; velocity, volume andvariety (data types), new problems emerge. Data volumes grow and data becomes unmanageable and immovable. Scalability, security, and information latency become new issues. Dealing with unstructured data, sensor data and spatial data all introduce new data type complexities.Traditional data analysis typically starts with a representative sample or subset of the data that is exported to separate analytical servers and tools (SAS, R, Python, SPSS, etc.) that have been especially designed for statisticians and data scientists to analyze data. The analytics they perform range from simple descriptive statistical analysis to advanced, predictive and prescriptive analytics.
IIC Approves Factory Automation Platform as a Service (FA PaaS) Testbed Proposed
IIC Approves Factory Automation Platform as a Service (FA PaaS) Testbed Proposed
Edge computing via local Edge controllers allows uniterrupted, high speed collection, filtering and processing of real time data line side. Initial fast reactions can be initiated with the full data sets also being sent to associated cloud systems for further analysis. This processing at two layers respects the data integrity but allows the collected data to be processed as live and historical instances. The challenge is how to collect the data from diverse sources without interrupting the existing processes but also being able to span "brown field" systems where there may not even be any existing communication or data capture functions. 

The global Smart Manufacturing Market is set for rapid growth and is expected to reach around USD 479.01 billion by 2023.

Source: Zion Market Research

What is the business value of this IoT use case and how is it measured?
Your Answer

How do automated manufacturing systems provide business value?

● Safer for Employees
● Increased Productivity (24/7 runtime)
● Improved Product Quality
● Higher Yields
● More Accurate Data Collection

Not only do automated industrial systems increase production capacity, but the quality of that production is improved, along with greater safety for the employees operating the equipment. These systems can also be configured to provide more accurate data to optimize weak points and greatly decrease product defects due to human error.

What are the benefits of MIcrogrids?

Provides power quality, reliability, and security  for end users and operators of the grid​

Enhances the integration of ditributed and renewable energy sources

Cost competitive and efficient

Enables smart grid technology integration

Locally controlled power quality

​Minimize carbon footprint and green house gas emissions by maximizing clean local energy generation​

Increased customer (end-use) participation

Which technologies are used in a system and what are the critical technology?
Your Answer

What are the latest trends in manufacturing technology?

New manufacturing technologies are continually emerging. Some of the biggest trends in recent years include:

  • 3D printing: enabling the creation of almost any component using metal, plastic and other materials, reducing lead time and streamlining the design-to-production process
  • Cloud services: enabling virtual sharing of data and services from any location quickly and efficiently
  • The Internet of Things (IoT): transforming not just the consumer market, but the maintenance and upkeep of electronic devices used in manufacturing processes as well
  • Nanotechnology: enabling things like faster computer processing, longer product lifecycles and super-precision manufacturing, and pioneering advancements in sectors such as space engineering and biotechnology
  • Advanced data analytics and predictive technologies: enabling better process control, prevention of defects and quicker response times in manufacturing
  • Industrial robotics: offering ways to increase productivity, improve quality and reduce cost by automating difficult or monotonous tasks
What business, integration, or regulatory challenges could impact deployment?
Your Answer

What is the biggest challenge face Manufacturing Sytem Automation?

● Cost of Initial Investment

There’s only one real downside to implementing automated manufacturing systems, which is the initial cost. This includes costs of machinery and implementing automated programming as well as training of employees to manage these new systems. However, ROI on this investment generally pays for itself within a few years.

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