ARC STRATEGIES
By Dick Slansky
JUNE 2015
The Smart Connected Factory of the Future
Executive Overview .................................................................... 3
The Future of Manufacturing: Smart, Connected, and Autonomous ... 4
Smart Connected Machines Will Drive Smart Connected Factories ...... 8
Value Proposition for the Smart Connected Factory ........................11
IIoT and Industrie 4.0: Common Goals for the Factory
of the Future ............................................................................14
Recommendations and Conclusions ..............................................17
VISION, EXPERIENCE, ANSWERS FOR INDUSTRY
ARC Strategies • June 2015
Other
Plant
Corp HQ
OEM
Maintenance Supply Chain
Supplier
IT
Distribution
Procurement
Plant Ops
Customer
Sales/Mktg
Industrial/
Retail Customer
Engr.
Service
Provider
Utilities
Smart Connected Factories Support New Value Chain Models
Maturity Model – IIoT Asset Capabilities
Autonomous
Added Value
Smart
Software
Defined
Instrumented
Conventional
• No intelligence
or connectivity
• Connectable
or connected
• Provides
data
externally
+ Some local
intelligence
+ Software
tunable asset
+ Enhanced
data feeds
+ Enhanced
intelligence
+ Active
condition
monitoring
+ Self
optimization
+ Interact with
ecosystem
IIoT Enabled
Level of Maturity
IIoT Maturity Model
2 • Copyright © ARC Advisory Group • ARCweb.com
+ SelfScheduling
+ Real-time
analytics
+ ProductProduction
Process
Interaction
+ Self-Healing
Systems
+ Decision
Making
Control
Systems
ARC Strategies • June 2015
Executive Overview
With the emergence of the Internet of Things (IoT), Industrie 4.0, Smart
Manufacturing, and other new approaches and initiatives, manufacturers
have to consider how they design the next generation of smart connected
products and the factories that will produce them.
Product designers must now consider an expansion of form, fit, and function to include connectivity and intelligence to be able to leverage the IoT
environment. The factories that manufacturer these products, in turn, will
have to be designed to take advantage of smart connected devices, machinThe smart connected product will
comprise the components that make up
intelligent systems in industry,
infrastructure, and business, and will
ery, systems, and business processes. In many cases, these smart “connections” will extend well
beyond the factory walls to value chain partners.
automate, operate, optimize, and
Suppliers and end users alike will also have to con-
maintain our factories and plants.
sider the impact on aftermarket services, since the
smart connected products, Big Data, and predictive
analytics components of the IIoT open up a new paradigm for how manufacturers support their products and equipment via remote diagnostics,
predictive analytics, and visualization “in the Cloud.” In some cases, rather
than selling and supporting a physical product, a piece of equipment, or
software application; suppliers will instead offer the respective functionality “as a service,” using the Internet as a delivery mechanism.
Another consideration is that service is the natural result of IoT. Both consumer products and industrial devices that are connected can intelligently
communicate their state, condition, or health so a service can be performed
to respond to the communication. This new generation of products will
have a significant impact on productivity and effectively reshape the value
chain by changing product design, marketing, manufacturing, and aftermarket service, along with creating the need for analytics and security.
These smart connected products will comprise the components that make
up the intelligent systems in industry, infrastructure, and business, while at
the same time, helping to automate, maintain, and optimize our factories
and plants.
While smart connected consumer products are basic elements of the overall
IoT; the smart, connected factory/plant will rely on the Industrial Internet of
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ARC Strategies • June 2015
Things (IIoT), a subset focused on the unique (and often more robust) requirements of industry and infrastructure.
This ARC Advisory Group report will explore the emergence of factories
that will manufacture the next generation of products and components using
smart,
connected
devices,
machines,
systems,
and
software
applications. The factory of the future will be built using these smart connected components and devices that will monitor, control, optimize, and
ultimately lead to the realization of the autonomous factory.
The next phase in this journey will be to develop and implement a semantic
IIoT framework to help unify control, monitoring, tasking, analysis, and
optimization of the production systems to provide a foundation for the autonomous factory of the future. The vision for the IIoT aims to bring
physical objects (in this case, components of factory/plant automation) into
the Internet environment. The primary focus of IIoT is to bridge the gap
between the physical and digital worlds of industry over a common and
widely used platform, the Internet.
The Future of Manufacturing: Smart,
Connected, and Autonomous
The “lights out” factory is often portrayed as the culmination of factory automation in which robots; automated production systems; and intelligent
machines, sensors, and equipment manufacture products without manual
human intervention. While the reality of the lights out factory remains in
While the reality of the lights out
factory remains in the future for
manufacturing, remarkable
the future, remarkable progress has been made in automating
the
production
process,
especially
in
industries like automotive, electronics and semiconduc-
progress has been made in
tor, and food and beverage packaging. Automation has
automating the production process.
evolved from moving production lines that ushered in
the era of mass production to complex robotic work
cells. These work cells are a marvel of integration and orchestration in
which robots are integrated with automated conveyance, tooling, fixtures,
and actuators that perform multiple assembly functions and tasks.
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Automation Remains a Key Component of the Smart
Factory
Today, manufacturers across many industrial sectors use highly automated
production systems that communicate across work cells and production
lines and push real-time production information to supervisory levels and
business intelligence applications. Automation suppliers have developed
vertical integration architectures that allow production data to flow upward from connected machines, production lines, work cells, and
Rather than relying solely on a vertical
architecture based on automation
systems, manufacturers have shifted
more to a horizontal architecture based
automation components to the control level (PLCs,
PACs, CNCs), manufacturing operations management (MOM) level and – ultimately -- to the
enterprise business level.
on the product lifecycle of design,
build, and operate.
The concept driving a vertical automation architecture was that real-time production data and the
actionable information that it would generate would move beyond the supervisory and MES layers to the enterprise business levels (SCM, CRM,
EAM, ERP) of a manufacturer. To date, this vision has not been fully realized.
Manufacturers understand the value of using real-time production data to
measure, monitor, and analyze production processes and optimize the production process. However, rather than relying solely on a vertical
architecture based on automation systems, manufacturers have shifted to a
more horizontal architecture based on the product lifecycle of design, build,
and operate. These vertical and horizontal axes intersecting at key points in
Design/Build/Operate Lifecycle
Product
Design
Systems
Engr.
Product
Test
Mfg. Process
Design
Production
Simulation
Automation
Production
Systems
Mfg. Operations
IIoT Encompasses the
Domains of Manufacturing Process
and Production
Supervisory Control
Automation, Control Systems
Sensors, Actuators, Motors, Servos
Machines, Work Cells, Production Equipment
Vertical Automation Integration
Automation Intersects with Design/Build Lifecycle to Enable the Digital Factory
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ARC Strategies • June 2015
the product, process, and production lifecycle to provide actionable information to help improve and optimize the overall production lifecycle
process.
Today’s horizontal design/build/operate lifecycle-based architecture promotes and enables the concept of the digital factory and enterprise. ERP,
SCM, SRM, and other enterprise software applications are integral parts of
the lifecycle from design to operations and depend on product, process,
and production information. Along with this connection to enterprise-level
business applications, product lifecycle now includes MES and MOM solutions. These production management applications are integrated with the
product design and manufacturing process domains of the product lifecycle.
By applying advanced analytics to production-related data, generated from
monitoring and measuring the execution of the production process, manufacturers can now finally realize continuous process improvements.
Looking ahead, analytics will also be one of the key enablers for monitoring, controlling, optimizing, and realizing the autonomous factory.
Smart Connected Factory Embodies a System of Systems
In manufacturing plants, high-value production equipment has been heavily instrumented for some time in a closed, hard-wired factory network
environment. However, industrial sensors, controllers, and networks are
costly to implement and upgrades to existing facilities are complicated projects that often interrupt production. The growth of IoT in the consumer
product sector has driven down the cost of sensors, embedded intelligence,
and communications interfaces through high volume semiconductor manufacturing. Conversely, industrial standard equipment continues to be
To make the transition to the next
generation of smart connected
factories, it will be necessary to
design and architect production
systems, automated work stations,
constrained by a very large installed base of legacy
equipment based on industry standards and proprietary
communications protocols.
To make the transition to the next generation of smart
and assembly lines into an
connected factories it will be necessary to design and
industrial “system of systems.”
architect production systems, automated work stations,
and assembly lines into a factory system of systems that
takes advantage of the less costly sensors, software, and communications
approaches initially targeted at the consumer IoT space. Much of this technology will be wireless and based on open standards. By connecting
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ARC Strategies • June 2015
machines to machines, people to machines, and machines and people to
expanded systems of systems, manufacturers can create intelligent networks and factory systems along the entire value chain. This will lead to
factory systems that communicate and control each other autonomously,
requiring significantly less operator intervention.
The concept of a system of systems is the natural extension of systems engineering and model-based design. The basic idea here is that today’s
factory and its production systems are most efficient and productive when
all elements and manufacturing processes are connected through intelligent
networks. This would start with automated production systems and all
connected sensors, controllers, devices, machines, and other production
equipment.
Improved factory visibility would come next, with HMI/SCADA, dashboards, and factory intelligence systems providing factory personnel with
actionable, real-time information. Mobility technology will further enhance
visibility, providing people with access to information beyond the production systems and even the factory’s walls. Access to real-time information
from anywhere and at any time can significantly shorten the time between
when a problem occurs and its resolution.
Connected asset management and maintenance would follow. While manufacturers generally understand the potential benefits of condition-based
predictive maintenance; most have yet to implement these advanced methods due to the cost associated with instrumenting key assets.
Today,
however, lower cost smart sensors, wireless connectivity and more advanced and easier to use analytics tools are making it less expensive and
easier to monitor and assess the health of factory equipment.
While just in time manufacturing processes have been an integral component of manufacturing for decades, IIoT in the form of advanced analytics
and connected intelligent machines and production systems is providing
manufacturers with enhanced understanding of supply chain information
that can be delivered in real-time. By connecting the production lines, machines, and factory equipment to their suppliers, all stakeholders across the
supply chain can better understand and respond to interdependencies, material flows, and manufacturing cycle times. IIoT-enabled systems can be
configured for location tracking, remote health monitoring, and reporting
of parts and components as they move through the supply chain. This will
power advanced analytics to help manufacturers identify and respond to
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ARC Strategies • June 2015
potential production issues before they occur. In some cases production
systems will be able to autonomously adapt to changing dynamic work
flow situations.
Smart Connected Machines Will Drive
Smart Connected Factories
The factories of the future will employ (largely wirelessly) connected machines, workstations, and production equipment to enable highly
individualized production on a large scale with high flexibility to support
IIoT-enabled intelligent factories
will be wirelessly interconnected in a system of cyberphysical machines, production
systems, and materials.
mass customization of products. In this IIoT-enabled production environment, intelligent factories will be interconnected in a system of cyber-physical machines, production systems, and materials.
Within an IIoT enabled
production environment the focus of manufacturers will be
on efficiency in terms of energy and workers, optimization
of production processes through continuous process improvement, and increasing productivity through advanced analytics. Additionally, products
being manufactured will communicate directly with the machines and
workstations performing the machining, fabrication, and assembly.
What Makes a Factory Smart?
Actionable information will be gathered in real time from intelligent sensors and other monitoring technology to provide current machine and
production system conditions, the state of the production process, work
flow, material and inventory, and all manner of data for analysis. Advanced analytics will use this information to help improve both production
and product quality, validate that the production systems are building the
product as designed, and identify optimization opportunities. Connectivity
and intelligence will allow factories to evolve from predictive methods to
prescriptive optimization and, ultimately, to autonomous operations.
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Monitoring
Sensors and external
data sources enable the
overall monitoring of :
 The machine, work cell,
production system’s
condition
 The external environment
 The production system’s
operational and
maintenance condition
Control
Autonomy
Optimization
Monitoring and Control
Software embedded in the
production systems enables: capabilities enable
 Control of machines and algorithms that optimize
production operations to:
production equipment
 Enable continuous
 Machine to Machine
process improvement
 Machine to System
 Allow predictive
 Operator to Machine
diagnostics and
 Control of overall
maintenance
production system
 Allow prescriptive
optimization methods
Combining monitoring,
control, and optimization
allows :
 Autonomous operations
 Self-coordination of
production operations with
the products and other
systems
 Autonomous process
enhancement and
improvement
 Self-diagnosis and service
Elements of the IIoT-Enabled Smart Factory
Next-generation smart factories incorporate many of the very same characteristics and capabilities possessed by the next-generation smart products
they manufacture. Intelligence and connectivity will enable an entirely new
set of functions and capabilities for both the products and the production
systems.
Smart Factory Functions and Capabilities
Four functional capabilities characterize the smart, connected factory: monitoring, control, optimization, and autonomy. Interestingly, each of these four
areas can be applied to both the smart product and the factory production
system that manufactures the product.
Monitoring
Monitoring, an essential first step, enables a comprehensive examination of
all factory components, including the current condition of and operational
parameters for all machines, workstations, production equipment, and other plant assets. This could also include monitoring external factors such as
raw material characteristics and the overall state of the supply chain. Established production methods such a just-in-time and Kanban would become
integrated into the overall production systems. To support this pervasive
monitoring, the next generation of connected intelligent sensors will provide real-time data and information. In some cases, the sensors themselves
will perform appropriate analysis, providing actionable information to operations.
Control
The element of control can be viewed in both the context of the product
(machines and devices) and the production system. Factory automation in-
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volves control at both the individual machine and production systems levels. While control systems are already a well-established and mature area in
most modern factories, the IIoT-enabled smart factory will exhibit greater
integration between control domains and increased connectivity with other
plant and enterprise systems.
Machines and production equipment, can be enhanced with embedded intelligence through smart sensors, adaptive control software, and even
awareness and self-healing capabilities. These machines can be regarded as
smart connected products that are components in a more complex production system.
In today’s factory production environment much of these characteristics of
control already exist in terms of machine to machine, operator to machine,
and machine to system interfaces. Intelligent sensors, for example, are fundamentally a smart connected product that become a component in higher
level systems that enable the collection of actionable information for even
higher level systems. Thus, an individual smart, connected product becomes an integral component of a system of systems, and, in this case
enables an IIoT environment that runs a factory ecosystem.
Optimization
While monitoring and control functions have traditionally worked in tandem to deliver both open and closed-loop control systems, the next primary
element in an IIoT environment, optimization, depends on monitoring and
control capabilities and data to actually optimize the production process.
This is where some of the fundamental principles of continuous process
improvement come into play, along with today’s more advanced analytics
engines employ algorithms to analyze the metrics and data from monitoring functions to enable predictive diagnostics that can anticipate equipment
and production problems before they actually occur. Bringing this one step
forward, advanced analytics can enable a prescriptive approach that not
only anticipates problems, but also prescribe the appropriate remedy or
remedies.
Autonomy
Autonomous production, still likely to be a bit further out into the future,
represents the final characteristics of the IIoT-enable smart, connected factory.
Monitoring, control, and optimization represent a continuum, with
autonomous production the end point in this continuum. With autono-
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mous production machines, equipment, and entire production systems operate autonomously with minimum, if any, human intervention.
This
includes human-free coordination between production systems and the
products being produced. Autonomous production systems will also feature self-healing production assets and systems.
The benefits of autonomous production systems acting in coordination with
other factory systems and the products being produced will grow in direct
proportion to the number of systems connected. For example, the energy
efficiency of the overall factory will increase as more production equipment
such as motors and energy consuming equipment is connected, monitored,
and analyzed to gain information on energy use.
Ultimately, all production systems will operate with complete or semiautonomy, applying algorithms that analyze Big Data related to performance, work flow, and the overall production/distribution ecosystem,
including other factories and the supply chain itself.
Value Proposition for the Smart
Connected Factory
IIoT has the potential to significantly transform many industrial sectors,
both in discrete and process manufacturing industries. Across the emerging IIoT ecosystem an extremely large number of machines and devices will
transmit both large and small amounts of data. Smart manufacturing comIntelligent factories will be wirelessly
inter-connected in a system of cyberphysical machines, production
systems, and materials within an
industrial IoT (IIoT) enabled
panies that want to compete successfully will use
advanced analytics to drive smarter decisions and
more efficient operations.
IIoT, Big Data analysis and connected networks will
production environment driven by
help manufacturers prolong their asset lifespan
actionable information.
while simultaneously optimizing efficiency and minimizing energy consumption. Smart manufacturing
systems will link production systems and business domains such as ERP
and supply chain planning. ARC has identified numerous potential business use cases for IIoT in manufacturing. Several examples follow.
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Production System Visibility and Business Intelligence
IIoT networks will connect real-time production activities on the plant floor
and associated data to enterprise business systems and decision makers
that must rely on actionable information. While this is certainly not a new
concept, the promise of IIoT is to provide production line information
based on a new generation of intelligent sensors, machines and systems. As
IIoT is adopted and implemented it will spawn the next generation of continuous process improvement (CPI) that will function more accurately and
correctly by using big data and advanced analytics. These IIoT enabled
production systems will harken back to the concept of event-driven manufacturing, where bottom-up collaborative production systems used
operations intelligence, visibility, demand-pull, and a synchronized supply
chain to drive the manufacturing process based on an intelligent eventoriented environment. The primary differentiator is that, today, IIoT provides a connected and intelligent system of systems to power event-driven
manufacturing.
Remote monitoring, advanced analytics, and improved visibility will provide benefits that extend beyond the enterprise to a wide range of suppliers
and third party providers of services, consumables, and capital goods. IIoT
systems will enable third-party suppliers to participate in and contribute to
the operations, maintenance, and optimization of manufacturing plants.
New business models will emerge, with many capabilities offers “as a Service,” and performance-based contracts utilizing remote monitoring and
support replacing traditional capital purchases of equipment and associated support services. Maintenance, repair and overhaul (MRO)-related parts
and services suppliers will use IIoT to monitor distributed inventories, the
condition of perishable parts, production rates, and so on. This will create
entirely new and closely linked business relationships between manufacturers and their equipment suppliers.
Energy Management
In many industries, energy is frequently the second or third largest operating cost behind materials and direct labor. However, many companies lack
the measurement systems, modeling tools, and/or performance management tools to optimize energy use in individual production operations,
much less across multiple operations, facilities, or an entire supply chain.
New, connected energy management solutions that incorporate IIoT-
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connected sensors and equipment, HVAC control systems, electrical control
systems, production control systems, and energy management systems offer numerous opportunities to create cost savings for manufacturers.
Connected energy solutions can help manufacturers reduce overall energy
consumption and avoid peak provide peak demand charges.
Some IIoT-
enabled HVAC systems also integrate weather data and prediction analysis
to help manufacturers understand expenses and plan energy usage accordingly. Energy analysts maintain that even relatively small improvements in
energy efficiency can often yield significant cost savings.
Predictive Maintenance
While most manufacturers today understand the potential benefits of condition-based maintenance — including both preventive and predictive
maintenance approaches — not very many have actually implemented
these advanced strategies to date, largely due to stranded assets, high connectivity costs, implementation costs, and uncertainty over the rapidly
changing technology.
Today, however, smarter, lower-cost sensors, wireless connectivity, and Big
Data processing tools make it cheaper and easier to collect performance data and monitor equipment health parameters, including both vibration and
temperature. Using these data, predictive asset management applications
can make maintenance schedulers aware of impending equipment failures
or gradual asset degradation so the issues can be addressed before they can
negatively impact production or product quality.
Predictive asset management based on real-time condition monitoring of
key production assets is a far more cost-effective approach than traditional
break/fix or calendar-scheduled preventive maintenance approaches. It
also improves both overall equipment effectiveness (OEE) and extends the
lifecycle of manufacturing assets to increase return on investment (ROI),
both key business metrics.
Measuring vibrations, as mundane as that appears to be, to detect out of
specification machines and equipment is a frequently cited example of condition monitoring. Businesses, particularly industrial businesses, lose
money when equipment fails. With next generation intelligent sensor information, IIoT connected technology can monitor, collect, and analyze data
to provide a manufacturer with information to improve overall equipment
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effectiveness (OEE), save money by minimizing equipment failure, and allow the company to perform planned maintenance based on predictive
condition monitoring.
Connected Supply Chain
Just in time manufacturing has been around for decades, but IIoT, analytics,
and production networks will help manufacturers improve visibility into
their end-to-end supply chains. By connecting the production line and balance of plant equipment to suppliers, all parties can better understand
interdependencies, material flows, and manufacturing cycle times. IIoTenabled systems can be configured to enable location tracking, remote
health monitoring of raw materials and finished goods inventories, and
track and report on parts and products as they move through the supply
chain.
IIoT-based systems can also collect and feed delivery information into an
ERP system; providing up-to-date information to sales and marketing
groups and into accounting functions for billing.
IIoT and Industrie 4.0: Common Goals
for the Factory of the Future
The Industrial Internet of Things and Industrie 4.0 concepts have different
origins, but many common objectives and technologies. IIoT began as a
IIoT is an industrial response to a
consumer-facing trend (the
generic Internet of Things), while
general phenomenon involving a global proliferation of
embedded sensors, data analytics, and networks with industrial applications. Industrie 4.0, on the other hand,
Industrie 4.0 is more particular to
began as a consortium between the German government,
industry and automation.
industry, research, industrial associations and industrial
unions. In other words, the IIoT is an industrial response
to a consumer-facing trend (the generic Internet of Things), while Industrie
4.0 is more focused on industrial automation, particularly as it applies to
manufacturing.
In the final analysis, the two terms refer to very similar movements and
both IIoT and Industrie 4.0 will certainly enable the smart connected factory
of the future.
Arguably, the intersection of the two concepts comes into
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particularly sharp focus in the smart connected factory, since Industrie 4.0
emphasizes flexible, highly automated production to support mass customization in manufacturing; while IIoT emphasizes smart, connected
industrial assets and advanced, cloud-based analytics to improve asset
availability and performance.
Cyber-Physical Production Systems
Industrie 4.0 represents a paradigm shift from centralized to de-centralized
smart manufacturing. Advanced embedded technologies that enable cyberphysical production systems support intelligent machine-to-machine, machine-to-human, and machine-to-production system communications. This
enables a fundamental shift from conventional industrial production to
connected, intelligent manufacturing through IIoT-enabled smart factories,
products, and services. Here, the boundaries between the virtual and physical worlds blur as factory simulation software validates and commissions
real machines and production systems communicating and functioning autonomously.
Production and supplier networks will become substantially more complex
in the next few years. For the most part, factory networks and production
processes have typically been limited to a single factory. But in an
IIoT/Industrie 4.0 scenario, the boundaries of individual factories will
begin to dissipate and eventually go away entirely.
Multiple factories
across the value chain will be interconnected, in some cases, even across
geographical regions, expanding the system of systems that represents a
single production system and factory into an even larger system of systems.
The manufacturing value chains will extend into both upstream suppliers
and downstream customers, all linked through the Internet to help ensure a
steady supply of raw materials and component parts when and where they
are needed and finished products with the correct options, packaging, and
labeling.
Additionally, in an IIoT/Industrie 4.0-enabled factory, condition monitoring and fault diagnosis, self-aware components and systems will work
together to provide operations and maintenance management with a more
accurate picture of the current status and overall health of production systems and equipment and enable them to effectively predict and prevent
future asset-or production-related issues and minimize, if not totally eliminate unnecessary maintenance to achieve near zero downtime.
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Intelligent Services for Smart Products
In today’s global industrial market, companies must manufacture reliable,
high-quality products that are attractive and useful to the consumer and
then be able to produce this product at a competitive cost. Many of these
The emergence of IIoT technologies and
models work in concert with the unified
lifecycle by connecting the
design/build/operate domains to allow an
same companies must also provide highquality support services for the products they
manufacture as an expected element of the
product lifecycle.
information continuum and feedback loop to
continuously improve and optimize both
To foster product loyalty, manufacturers will
manufacturing processes and product design.
need to produce products that will be connected and intelligent. Product lifecycles will
extend beyond the walls of the factory. Within the service lifecycle, smart
products will monitor their own condition and health and report these back
to the manufacturer, in some cases, triggering remote maintenance, reconfiguration, software updates, and/or technician visits, as appropriate.
Manufacturers could also use this product information to analyze and determine improvements to the product design and the manufacturing
processes.
IoT, IIoT, and Industrie 4.0 will work in concert to provide multiple levels
and sources of connectivity and intelligence that will support an end-to-end
product, process, and production ecosystem.
Unified Product Lifecycle Management
A significant emerging trend in manufacturing is the unified, end-to-end
lifecycle that extends from product design through production execution.
Today’s product lifecycle management (PLM) solution providers typically
offer applications that cover all domains of the design/build/operate/
service lifecycle. Many manufacturers across a range of industries have
adopted this approach and developed product, process, and production
models and methods to support a unified product lifecycle.
IIoT technologies and models work in concert with the unified lifecycle by
connecting the design/build/operate domains to allow an information continuum and feedback loop to continuously improve and optimize both
manufacturing processes and product design. Adopting IIoT technologies
and methods should be a relatively straightforward transition for manufacturers with a unified lifecycle environment.
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Recommendations and Conclusions
The factory of the future will be characterized by the convergence of the
digital and physical worlds. Embedded software that provides intelligence,
connected machines and production systems that can be monitored and
Companies will be compelled to
orchestrate an ecosystem of design
innovation, production process
collaboration, operation and
maintenance, suppliers, partners and
analyzed to optimize processes, and factories and
plants that will run autonomously will mark the
next evolutionary step in manufacturing and process industries.
contractors, dealers and distributors, and
Manufacturers entering this era of smart connect-
customers in preparation for the IIoT.
ed factories should make a concerted effort to
understand the technologies that will drive IIoT
and understand the overall ecosystem of connected, intelligent products
and manufacturing processes and how this will affect the consumers of
their products.
IIoT represents a departure from traditional value chains. Companies will
be compelled to orchestrate an ecosystem of design innovation, production
process collaboration, operation and maintenance, suppliers, partners and
contractors, dealers and distributors, and customers.
To support this transition, companies need to be aware of four key elements
of IIoT: industrial automation, analytics, embedded intelligence, and the service
lifecycle. Industrial automation -- including both sensor and control networks -- will provide a portion of the connectivity infrastructure for IIoT.
This will enable manufacturers to leverage their existing investments in industrial software and automation, to a large degree.
The rapid maturation of Big Data analytics is changing the face of manufacturing, which looks and feels very different today than it did even a decade
ago. Historically, companies have made significant investments in information technology to connect to plant floor operations, but have not
generally realized the full potential. IIoT-based Big Data and advanced analytics will deliver on the promise of IT in manufacturing through
continuous process improvements.
Embedded intelligence in all machines, equipment, and production systems
will be a key element in implementing IIoT in smart connected factories,
enabling them to move into the optimized and – ultimately – autonomous
operating modes. Embedded intelligence in all aspects of the production
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ARC Strategies • June 2015
systems, as well as in the product itself is critical to the predictive, prescriptive, and autonomous phases that will define the factory of the future.
Finally, the natural extension of the smart connected factory is the service
lifecycle of the product itself. As industrial devices and equipment become
more intelligent and connected, they produce large volumes of data. The
information generated shape a range of new data- and service-based business models. This emerging service lifecycle can be applied to the
production equipment and factory/plant assets, as well as consumer-facing
products.
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Analyst: Dick Slansky
Editor: Paul Miller
Distribution: MAS and EAS Clients
Acronym Reference: For a complete list of industry acronyms, please refer
to www.arcweb.com/research/Lists/IndustryTerms/.
CPI
Continuous Process
MRO Maintenance, Repair, and
Improvement
CNC
Overhaul
Computer Numerical Control
CRM Customer Relationship
OEE
Overall Equipment Effectiveness
OEM Original Equipment Manufacturer
Management
PAC
EAM Enterprise Asset Management
Programmable Automation
Controller
ERP
Enterprise Resource Planning
PLC
Programmable Logic Controller
HMI
Human Machine Interface
PLM
Product Lifecycle Management
IIoT Industrial Internet of Things
ROI
Return on Interest
IoT
Internet of Things
SCADA Supervisory Control and Data
IT
Information Technology
MES
Manufacturing Execution System
Acquisition
MOM Manufacturing Operations
Management
SCM
Supply Chain Management
SRM Supplier Relationship
Management
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