Understanding Digital Reliability

1
Understanding Digital Reliability
Manufacturing industries manage complex
production environments where even a single hour
of downtime caused by unreliable or unavailable
assets can cost the manufacturer millions. Not
to mention, there are added risks of hazardous
leaks, life-endangering accidents, and a
complete breakdown of the value chain. One of the
reasons behind the uptake of Industry 4.0
technologies and systematic digital
transformation is the need to overcome this
inherent uncertainty in discreet and process
plants. Intelligent automation and advanced
analytics can enable operation and maintenance
teams to improve asset availability in their
plants. Furthermore, mission-critical assets can
be made more reliable, helping plant teams
achieve intended targets and objectives. This is
why theres an increasing shift in focus toward
digital plant reliability and manufacturing
leaders are prioritizing the adoption of
technologies that can drive these
objectives. This article will cover what
digital reliability is, what are its benefits,
and which technologies are driving digital
reliability in manufacturing industries.
What is Digital Reliability? Reliability is the
probability of a system meeting certain
pre-defined performance standards and delivering
desired output for an intended period of time. A
reliable system continues to perform within
specific parameters, without experiencing any
anomalies or breakdowns and operates at optimum
productivity level. Digital reliability is
ensuring asset and plant reliability through
smart digitalization of processes and increased
data availability to support decision-making. Co
ntemporary digital reliability solutions rely on
real-time condition monitoring of manufacturing
equipment, performing predictive analytics on
collected data, and mapping the machine
performance to generate a realistic health status
of the asset. Data irregularities are
investigated to diagnose existing or potential
faults, and take corrective measures to mitigate
the risk of failure.
2
Take a steel manufacturing plant, for instance,
where a cold rolling mill is critical equipment
that controls the production flow and throughput
quality. The asset is responsible for achieving
greater dimensional accuracy and increasing the
hardness of the final product. If a cold rolling
mill is available but not functioning under
optimal conditions, then potential breakdown can
lead to several hours of production downtime.
With digital reliability measures, this
eventuality can be avoided and the cold rolling
mill can become highly reliable, saving over 72
hours of production downtime. (Read the full
case here.)

• Predictive Maintenance for Digital Reliability
• More than 70 of equipment breakdown is due to
  mechanical faults, including equipment wear,
  deterioration, backlash, increase in clearances,
  vibrations, and acoustics. While for hydraulics,
  thermal and electrical faults, standard
  monitoring solutions are available, for
  mechanical faults, monitoring becomes
  challenging. To drive digital reliability
  objectives in these scenarios, predictive
  maintenance becomes an important enabler.
• With Predictive Maintenance (PdM), plant
  maintenance teams can estimate the exact
  remaining useful life (RUL) of the equipment
  perform accurate diagnostics, and receive
  insightful recommendations to strategically plan
  maintenance activities. Real-time monitoring of
  triaxial vibrations, acoustics, and surface
  temperature is utilized to generate digital
  reliability reports and guide maintenance
  schedules. Responsive predictive maintenance
  solutions can also
• Adapt to special production conditions
• Diagnose high-frequency data
• Accurately decipher the signal from noise
• Overcome complex bandwidth limitations
• Collect and store multi-location data on-cloud

3
To Know more about Digital Reliability https//ww
w.infinite-uptime.com/understanding-digital-reliab
ility/