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Journey to Industry 4.0
and beyond with
Cognitive Manufacturing
2
We’re entering the fourth revolution of industry and it is fully differentiated
from any that came before it
Line
Production
Electrification &
Automation
Miniaturization &
Global Scale
Cognitive
Manufacturing
Complexity
Era
1783
1870
1960
2020
Water, steam, and
conveyors; modern
materials handling
Assembly systems:
Lighting, electricity
and assembly lines
Embedded
systems:
Semiconductors,
computers,
information
technologies and
increase in trade
Cyber-physical
systems: sensors,
big data, predictive
analytics, cognitive
computing, cyber-
physical systems,
robotics, 3D
printing
3
collected manufacturing
and enterprise data
Smarter
Supply Chain
Management
Smarter
Energy
Smarter
Factory
Operations
Smarter
Product
Design
Smarter
Employee
Safety
Smarter
Quality
made into a transparent,
comprehensive,
interactive, minable corpus
of information
that makes visible new
patterns in the data
to continuously monitor,
predict, respond and
interact with humans and
machines
To deliver
Smarter
Equipment
Maintenance
Cognitive Manufacturing applies cognitive capabilities to digitize and
optimize previously inaccessible areas of manufacturing processes
4
To capture the potential of the cognitive manufacturing transformation,
we focus on three key pillars of manufacturing that drive the highest
improvement
Intelligent
Asset and
Equipment
Smarter
Resources and
Optimization
Cognitive
Process and
Operations
5
Intelligent Assets and Equipment
Intelligent assets and equipment utilizes IoT and cognitive capabilities to
sense, communicate and self-diagnose issues so they can optimize their
performance and reduce unnecessary downtime
 Prevent production delays and improve line
performance with better asset visibility
 Reduce equipment downtime and increase
process efficiency with industry models
 Expedite equipment repairs through
predictive and cognitive analytics
Decrease in equipment
downtime at major
global auto manufacturer
34%
6
Auto manufacturers are utilizing the
analytics capabilities of Watson IoT
combined with new sources of real-time
data to gain new predictions and
prescription on improving equipment
availability and performance. Using prebuilt
industry models, manufacturer can spend
less to analyzing and more time doing.
7
Equipment downtime can be significantly
reduced by combining the power of IoT
with cognitive capability. Not only can
Watson IoT predict what and when failures
can happen, it can utilize cognitive
capabilities to advise a user on exactly how
to fix and resolve these failures.
8
Cognitive Process and Operations
Cognitive operations and processes bring more certainty to business by
analyzing a variety of information from workflows, context and environment to
drive quality, enhance operations and decision-making.
 Increase yield of your manufacturing
operations and processes
 Improve productivity of your manufacturing
line with early quality detection
 Expedite service calls and repairs and reduce
warranty costs
Increase in overall
productivity at major
European automaker
25%
9
With quality analytics from Watson IoT
manufacturers can analyze hundreds of
process variables, historic and real-time, to
identify issues contributing to quality issues
and resolve them before they occur. This
drastically improves productivity and yield
while reducing operation and material
costs.
10
By utilizing cognitive capabilities, Watson
IoT can bring in unstructured data such as
image and video which enriches the
information around manufacturing
processes. Combined with other IoT data,
this information can produce more
accurate predictions and better insights
11
Smarter Resource and Optimization
Utilize IoT and cognitive insight to optimize the resources engaged around
production, whether that’s keeping production line workers safe, improving the
expertise of the entire workforce or optimizing energy consumption
 Improve worker safety and gain better
workforce management
 Increase worker productivity and expertise
 Reduce energy consumption of your facilities
and buildings
Reduced energy and
resource costs at
manufacturing facility by
8%
12
Industrial manufacturers are using Watson
IoT to help employees stay safer in
dangerous environments. The solution
detects hazardous environments and
provides real-time alerts to employees and
employers enabling preventive measures if
physical well-being is compromised or
safety procedures have not been applied.
13
Engineers are training Watson to collate
30+ years of engineering experience in
managing liquid gas facilities to create a
cognitive advisory service to help
employees across the organization resolve
problems faster, improve process flow and
achieve better operational outcomes.
14
Embracing cognitive manufacturing
Collect the
Data
Collect and curate the
right data— data on
processes and
operations you would like
to improve, data across
your systems, both
structured and
unstructured. Connect
systems and sensors to
bring in real-time data for
more accurate insights
Visualize the
Patterns
Visualize your data on a
platform. Quickly build up
dashboards and use
simple analytics to
determine patterns.
Supplement with external
sources of data and
analyze variables that
impact the process and
operation you would like
to improve.
Analyze with
Purpose
Apply purpose driven
analytics to gain new
insights from you data
Developed advanced
models, process a
combination of variables
and utilize the prediction
engine to generate the
best recommendations
the drive the most
business results
Deliver with
Cognitive
Whether it’s dealing with
vast amounts of IoT data
or dark and unstructured
data, cognitive
capabilities brings light
and clarity. Take
advantage of the
processing power of
cognitive to enable you to
act, resolve, and deliver
better
15
Differentiating elements of Watson IoT technology and ecosystem
Partnered
Innovation
Open ecosystem
Device partnerships
Embedded security
Edge Analytics
Data
Integration
Weather data
Social data
Application data
Platform of platforms
Advanced
Analytics
Predictive Analytics
Real-time Analytics
Data Mining
Optimization
Cognitive
Technology
Natural Language Processing
Machine Learning
Textual Analytics
Video/Image Analytics
Journey to Industry 4.0 and beyond with Cognitive Manufacturing

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Journey to Industry 4.0 and beyond with Cognitive Manufacturing

  • 1. Journey to Industry 4.0 and beyond with Cognitive Manufacturing
  • 2. 2 We’re entering the fourth revolution of industry and it is fully differentiated from any that came before it Line Production Electrification & Automation Miniaturization & Global Scale Cognitive Manufacturing Complexity Era 1783 1870 1960 2020 Water, steam, and conveyors; modern materials handling Assembly systems: Lighting, electricity and assembly lines Embedded systems: Semiconductors, computers, information technologies and increase in trade Cyber-physical systems: sensors, big data, predictive analytics, cognitive computing, cyber- physical systems, robotics, 3D printing
  • 3. 3 collected manufacturing and enterprise data Smarter Supply Chain Management Smarter Energy Smarter Factory Operations Smarter Product Design Smarter Employee Safety Smarter Quality made into a transparent, comprehensive, interactive, minable corpus of information that makes visible new patterns in the data to continuously monitor, predict, respond and interact with humans and machines To deliver Smarter Equipment Maintenance Cognitive Manufacturing applies cognitive capabilities to digitize and optimize previously inaccessible areas of manufacturing processes
  • 4. 4 To capture the potential of the cognitive manufacturing transformation, we focus on three key pillars of manufacturing that drive the highest improvement Intelligent Asset and Equipment Smarter Resources and Optimization Cognitive Process and Operations
  • 5. 5 Intelligent Assets and Equipment Intelligent assets and equipment utilizes IoT and cognitive capabilities to sense, communicate and self-diagnose issues so they can optimize their performance and reduce unnecessary downtime  Prevent production delays and improve line performance with better asset visibility  Reduce equipment downtime and increase process efficiency with industry models  Expedite equipment repairs through predictive and cognitive analytics Decrease in equipment downtime at major global auto manufacturer 34%
  • 6. 6 Auto manufacturers are utilizing the analytics capabilities of Watson IoT combined with new sources of real-time data to gain new predictions and prescription on improving equipment availability and performance. Using prebuilt industry models, manufacturer can spend less to analyzing and more time doing.
  • 7. 7 Equipment downtime can be significantly reduced by combining the power of IoT with cognitive capability. Not only can Watson IoT predict what and when failures can happen, it can utilize cognitive capabilities to advise a user on exactly how to fix and resolve these failures.
  • 8. 8 Cognitive Process and Operations Cognitive operations and processes bring more certainty to business by analyzing a variety of information from workflows, context and environment to drive quality, enhance operations and decision-making.  Increase yield of your manufacturing operations and processes  Improve productivity of your manufacturing line with early quality detection  Expedite service calls and repairs and reduce warranty costs Increase in overall productivity at major European automaker 25%
  • 9. 9 With quality analytics from Watson IoT manufacturers can analyze hundreds of process variables, historic and real-time, to identify issues contributing to quality issues and resolve them before they occur. This drastically improves productivity and yield while reducing operation and material costs.
  • 10. 10 By utilizing cognitive capabilities, Watson IoT can bring in unstructured data such as image and video which enriches the information around manufacturing processes. Combined with other IoT data, this information can produce more accurate predictions and better insights
  • 11. 11 Smarter Resource and Optimization Utilize IoT and cognitive insight to optimize the resources engaged around production, whether that’s keeping production line workers safe, improving the expertise of the entire workforce or optimizing energy consumption  Improve worker safety and gain better workforce management  Increase worker productivity and expertise  Reduce energy consumption of your facilities and buildings Reduced energy and resource costs at manufacturing facility by 8%
  • 12. 12 Industrial manufacturers are using Watson IoT to help employees stay safer in dangerous environments. The solution detects hazardous environments and provides real-time alerts to employees and employers enabling preventive measures if physical well-being is compromised or safety procedures have not been applied.
  • 13. 13 Engineers are training Watson to collate 30+ years of engineering experience in managing liquid gas facilities to create a cognitive advisory service to help employees across the organization resolve problems faster, improve process flow and achieve better operational outcomes.
  • 14. 14 Embracing cognitive manufacturing Collect the Data Collect and curate the right data— data on processes and operations you would like to improve, data across your systems, both structured and unstructured. Connect systems and sensors to bring in real-time data for more accurate insights Visualize the Patterns Visualize your data on a platform. Quickly build up dashboards and use simple analytics to determine patterns. Supplement with external sources of data and analyze variables that impact the process and operation you would like to improve. Analyze with Purpose Apply purpose driven analytics to gain new insights from you data Developed advanced models, process a combination of variables and utilize the prediction engine to generate the best recommendations the drive the most business results Deliver with Cognitive Whether it’s dealing with vast amounts of IoT data or dark and unstructured data, cognitive capabilities brings light and clarity. Take advantage of the processing power of cognitive to enable you to act, resolve, and deliver better
  • 15. 15 Differentiating elements of Watson IoT technology and ecosystem Partnered Innovation Open ecosystem Device partnerships Embedded security Edge Analytics Data Integration Weather data Social data Application data Platform of platforms Advanced Analytics Predictive Analytics Real-time Analytics Data Mining Optimization Cognitive Technology Natural Language Processing Machine Learning Textual Analytics Video/Image Analytics

Notes de l'éditeur

  1. We’re entering the fourth revolution of industry, the Cognitive Manufacturing era, and it is fully differentiated from any that came before it Digital transformation of production processes create new opportunities to achieve levels of productivity and specialization not previously possible Benefits include: Higher automation and productivity of manufacturing process Increased quality and competitiveness across the value chain Ability to create new markets by establishing new services and business models
  2. Yield = scrap Productivity is expected at standard cost and lots of moving parts to address – Foxconn has been muscling things with cheap labor but now they’re figuring out their labor base is not sustainable – at people or price. On paper you can always make your plan. collected manufacturing and enterprise data transparent, comprehensive, interactive, minable corpus of information makes visible new patterns in the data continuously monitor, predict, respond and interact with humans and machines to drive optimized performance
  3. Connected manufacturing is all about how you can utilize IoT to drive more efficiency in your “people, process and things” – thereby lowering cost Intelligent assets – optimizes “things” or equipment on the plant floor. This entry point focuses on the reliability metric, reducing downtime and focuses on aspects of predictive maintenance, asset performance. Cognitive process/operation – optimizes “processes” to drive higher yield. This entry point focuses on the quality metric, increasing yield and focuses on aspects of predictive quality and predictive warranty. Smarter resources – optimizes “people” to drive higher efficiency. This entry point focuses on cost efficiency, improving worker safety and workforce productivity, as well as improved energy management. The manufacturing machine health pilot was able to develop models to accurately predict 34% of machine failures @ global manufacturer of automobiles and a variety of motorized equipment (GM) 25% increase in overall productivity of cylinder-head line @ Daimler 8% energy cost reduction @ IBM Armonk facility
  4. Intelligent Asset and Equipment focuses on making the equipment on your shop floor smarter, more reliable and performing more optimally so you can reduce downtime and increase performance. We have to ability to make sense of your shop floor equipment by connecting your equipment through our IoT platform and edge partners and ecosystem. Whether you have PLCs (programmable logic controls) or sensors or manufacturing gateways our IoT platform can help you bring that data together so that you can visualize the effectiveness of your equipment. Beyond just visualization, you can take advantage of our advanced analytics that can provide predictions based on specific use cases such as maintenance or quality. Our new Plant performance Analytics which will GA in October come preloaded with valuable industry models for automotive – specific to body and weld – that can help you jump start your analysis. To move beyond analytics, you can utilize our cognitive capabilities such as NLP or image and text analytics in advanced cognitive use cases such as Equipment advisor (where ingested text from manuals/logs can help suggest ways to remedy issues)
  5. Cognitive Process and Operations is all about discovering insights on your current process so that quality issues are address early in the manufacturing process – significantly lower your costs of production and maximizing raw materials. Similar to intelligent assets, we offer connectivity and edge analytics through our platform and ecosystem. From there we can apply quality and warranty analytics that can detect the correlation between many variables that contribute to process failure or quality issues. These predictions are far superior to SPC (statistical process control) and can provide a prediction of failure earlier than SPC, allowing you to proactively administor actions so that you don’t suffer the loss when the failure occurs. In the field, these detections of quality issues can allow you to adjust your warranty. Again, taking a step further with cognitive capabilities, predictive quality can combine with image or audio analytics determine issues from these kinds of unstructured data.
  6. Smarter resource and optimization is about getting the most out of your resources which could be individual employees, an entire workforce or even things like energy. By connecting sensors outfitted on workers, we can detect if they are in hazardous conditions which allows supervisors to alert the employees, providing safer work environments. We can also combine a worker’s expertise with the effectiveness/quality of his tools to determine if we have the right worker/tool combo to get the work done. Furthermore, you can also leverage our Tririga tools in environment and energy management capabilities to reduce the consumption of energy in your factory facilities.