How smart manufacturing can optimize your factories for the new era

The focus of every industrial revolution has been increasing the productivity of production systems. The fourth industrial revolution is here, and it’s seeking to improve both production and management systems. Digital transformation driven by smart manufacturing (also known as Industry 4.0) is the basis of this latest one – creating opportunities to achieve levels of productivity and specialization not previously possible.

Combining data generated through the Industrial Internet of Things (IIoT) and analytics creates a new set of capabilities known as predictive maintenance and quality. Fueled by smart manufacturing, these new capabilities are changing the way we do and see business, helping recognizing patterns and predicting failures or product quality issues before they happen.

Are you on track to make smart manufacturing a priority?

A timeline of industrial revolutions
Crank icon
1st
1800
Mechanization, water
power, stream power
Factory icon
2nd
1900
Mass production,
assembly line,
electricity
A robot arm icon
3rd
2000
Computer and
automation
Robot icon
4th
Today
Cyber physical
systems

Introducing the new industrial IoT platform

Most factories are composed of operation technology (OT) assets such as machines, equipment lines and robotic devices that aren’t always connected. The current trend is leaning toward smart manufacturing with a more IT-based factory floor to help save time, labor, cost and maintenance and upkeep. With OT and IT converging, the IIoT platform is emerging as a new, innovative concept for smart manufacturing with artificial intelligence (AI)-based technologies, including analytics, big data and cognitive manufacturing.

Smart manufacturing can spur a new surge of manufacturing productivity.

Targeting the pain points for key manufacturing personnel

In order to understand the impact of Industry 4.0 solutions, we must examine the key people involved in all aspects of a factory. True transformation happens when all unique challenges and each pain point is targeted.

Icon of a maintenance manager
Maintenance manager
(scheduled maintenance)
Icon of a manufacturing operator
Manufacturing operator
Key manufacturing personnel in an IIoT ecosystem
Icon of a plant manager
Plant manager
Icon of a technician
Technician
diagnostics, repair,
installation
Icon of a maintenance manager and engineer
Maintenance manager
& engineer

Transforming your factory with a three-tiered architecture solution from IBM

Keeping the needs of different types of workers in mind and using our extensive manufacturing experience, IBM developed a three-tiered distributed architecture to implement smart manufacturing more efficiently. The model addresses the autonomy and self-sufficiency requirements of each production site and balances the workload between the three tiers.

Mapping IBM's three-tiered architecture for industrial manufacturing
Enterprise
world
Digital representation of the world (twin)
two people
External partners
group people
Users
Plant/Factory
Plant Service Bus
Edge
OT/IT connectivity
SCADA
PLC
PLC
Industrial equipment
MES
Applications
IIoT gateway
  1. Edge level. The most physical part of the factory where product-related activities are performed.
  2. Plant or factory level. Where plant and local activities are orchestrated and connected.
  3. Enterprise level. Where analysis of all levels of information happens, and information storage for visualization and analytics is provided.

Leveraging the three architecture tiers to drive performance

IBM offers a suite of enterprise asset management (EAM) solutions to help drive cost savings and operational efficiency across the factory value chain. The portfolio of EAM solutions from IBM analyzes a variety of information from workflows, context and the environment to drive quality and enhance operations and decision making. The portfolio of EAM solutions from IBM helps deliver a smart manufacturing transformation.

Production quality insights use IoT and cognitive capabilities to sense, communicate and self- diagnose issues to optimize each factory’s performance and reduce unnecessary downtime. Insights help reduce unplanned downtime.

IBM and Red Hat® can also be leveraged to deliver a hybrid multicloud platform for Industry 4.0. Together, IBM and Red Hat deliver a next-generation hybrid multicloud platform. By combining the power and flexibility of Red Hat open hybrid cloud technologies with the scale and depth of IBM innovation and industry expertise, any company engaged in an Industry 4.0 project can have access to the top tools and talent of both companies.

The four-step road map
1
Gather the data

Instrument your equipment/assets to collect data

Gather preexisting data

2
Visualize
the patterns

Visualize your data in meaningful dashboards

Start to see patterns

Build with Bluemix

3
Advance to
analytics &
digitalization

Gain insights from the data, produce models, predict recommendations

Streamline business processes

4
Infuse with
cognitive

Refine models with
cognitive machine
learning

Use other cognitive
functions to improve
engagement

In the white paper, you can read the full stories of how those we work with are succeeding in smart manufacturing:

Case Study 1: Implementing edge-level solutions to harness machine learning in automotive assembly

Case Study 2: Using the factory-level solution from IBM to manage assembly and detect deviations across several plants

Case Study 3: Implementing an enterprise-level solution from IBM to increase overall equipment effectiveness (OEE) in several manufacturing plants

How to deploy Industry 4.0 in your organization

Adding smart manufacturing solutions from IBM makes your manufacturing ecosystem flexible, fast and resilient. The IBM Industry 4.0 strategy brings value by collecting more data to optimize performance and improve agility in both short and long production runs.

Conclusion

For more information on how to digitally transform your factory and protect your cyber assets, please download the IBM white paper “IBM Industry 4.0 & Cognitive Manufacturing: Architecture Patterns, Use Cases & IBM Solutions” by Serge Bonnaud, Christophe Didier and Arndt Kohler.

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