SORBA IoT Case Studies Automated Predicitive Analytics For Steel/Metals Industry

	Automated Predicitive Analytics For Steel/Metals Industry SORBA IoT

Automated Predicitive Analytics For Steel/Metals Industry

SORBA IoT

Technology Category	Analytics & Modeling - Predictive Analytics Application Infrastructure & Middleware - Data Exchange & Integration Automation & Control - Programmable Logic Controllers (PLC) Functional Applications - Enterprise Asset Management Systems (EAM) Sensors - Pressure Sensors
Applicable Industries	Metals
Applicable Functions	Maintenance
Use Cases	Predictive Maintenance
Challenge	Asset to be monitored: Wire Compactor that produces Steel Rebar Customer Faced The Following Challenges: Dependent upon machine uptime. Pressure cylinders within the compactor fail to control compression and speed causing problems in binding the coil. Equipment failure occurs in the final stage of production causing the entire line to stop, can you say bottleneck? Critical asset unequipped with sensors to produce data. Read More
About Customer	A Steel Manufacturing Plant Produces Ponstruction Grade Rebar. 24 Hours a Day, 7 Days a Week, Scrap Metal is Converted into Steel. Each Year the Plant Produces 1.1 Billion Pounds of Steel Rebar Used in Concrete. That’s Enough Rebar to Circle the Glo Read More
Customer Name	Undisclosed Read More
Solution	The Results: SORBA-SDC (Smart Data Collector) connected to a Siemens PLC, collecting months of time series data to analyze behavior of equipment. Eliminated unplanned downtime for critical plant assets. Improved asset utilization rates, thus optimizing or reducing CapEx/OpEx costs. Minimized cost but not engaging IT personnel to connect into the enterprise network. SORBA does not require any firewall ports to open. Detected anomalies with lead times up to 20 days. Correlated all potential issues with work order events. Achieved an operational savings, in one application, of over $100,000 annually at just one site. Read More Log in to view content
Data Collected	Downtime, Equipment Status, Fault Detection, Machine Performance, Process Procedure Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Predictive Analytics

Application Infrastructure & Middleware - Data Exchange & Integration

Automation & Control - Programmable Logic Controllers (PLC)

Functional Applications - Enterprise Asset Management Systems (EAM)

Sensors - Pressure Sensors

Applicable Industries

Metals

Applicable Functions

Maintenance

Use Cases

Predictive Maintenance

Challenge

Asset to be monitored: Wire Compactor that produces Steel Rebar

Customer Faced The Following Challenges:

Dependent upon machine uptime.
Pressure cylinders within the compactor fail to control compression and speed causing problems in binding the coil.
Equipment failure occurs in the final stage of production causing the entire line to stop, can you say bottleneck?
Critical asset unequipped with sensors to produce data.

About Customer

A Steel Manufacturing Plant Produces Ponstruction Grade Rebar. 24 Hours a Day, 7 Days a Week, Scrap Metal is Converted into Steel. Each Year the Plant Produces 1.1 Billion Pounds of Steel Rebar Used in Concrete. That’s Enough Rebar to Circle the Glo

Customer Name

Undisclosed

Solution

The Results:

SORBA-SDC (Smart Data Collector) connected to a Siemens PLC, collecting months of time series data to analyze behavior of equipment.
Eliminated unplanned downtime for critical plant assets.
Improved asset utilization rates, thus optimizing or reducing CapEx/OpEx costs.
Minimized cost but not engaging IT personnel to connect into the enterprise network.
SORBA does not require any firewall ports to open.
Detected anomalies with lead times up to 20 days. Correlated all potential issues with work order events.
Achieved an operational savings, in one application, of over $100,000 annually at just one site.

Data Collected

Downtime, Equipment Status, Fault Detection, Machine Performance, Process Procedure

Impact #1	[Cost Reduction - IT] Minimized cost but not engaging IT personnel to connect into the enterprise network.
Impact #2	[Data Management - Data Collection] SORBA-SDC (Smart Data Collector) connected to a Siemens PLC, collecting months of time series data to analyze behavior of equipment.

Impact #1

[Cost Reduction - IT]
Minimized cost but not engaging IT personnel to connect into the enterprise network.

Impact #2

[Data Management - Data Collection]
SORBA-SDC (Smart Data Collector) connected to a Siemens PLC, collecting months of time series data to analyze behavior of equipment.

Benefit #1	Achieved an operational savings, in one application, of over $100,000 annually at just one site.
Benefit #2	Detected anomalies with lead times up to 20 days. Correlated all potential issues with work order events.
Benefit #3	Eliminated unplanned downtime for critical plant assets thus Improving asset utilization rates while also optimizing/reducing CapEx/OpEx costs.

Benefit #1

Achieved an operational savings, in one application, of over $100,000 annually at just one site.

Benefit #2

Detected anomalies with lead times up to 20 days. Correlated all potential issues with work order events.

Benefit #3

Eliminated unplanned downtime for critical plant assets thus Improving asset utilization rates while also optimizing/reducing CapEx/OpEx costs.

Partners	VMware (DELL)

Partners

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Overview

Automated Predicitive Analytics For Steel/Metals Industry

Operational Impact

Quantitative Benefit

Technology