Performance Monitoring & Real Time Event Action Reporting RITZ Automation will take all of your disparate systems & data and make them into actionable real time event reporting. This will decrease operational costs and increase employee efficiencies and profitability. Performance metrics is used to monitor equipment & material use as a part of real time information systems. Our systems design will provide you with critical insight into how well you are managing your operations.

1. RITZ Automation
Predictive
Analytics
Free
Evaluation
( 1 hr Tel)
Date: 02/14/13
Pages 1-6
Benefits & Example
What’s in your BIG data?
Are you using real time data
analytics to reduce costs and
downtime?
Industrial Data
System RITZ Automation will take all of your disparate systems • BI– Reporting Tools
Integrators & data and make them into actionable real time event • MES Mfg Exec Systems
reporting. This will decrease operational costs and • ERP - Enterprise Mgt
increase employee efficiencies and profitability. • CRM– Customer Mgt
PREDICTIVE ANALYTICS is understanding the area of • CMMS– Maintenance
greatest need, the highest criticality equipment with an
RITZ Automation • Data Analytics
unacceptably high rate of premature failures. It is based
• HMI - Operator Interface
upon root causes of failure of all critical production-
• Historian & Plant Metrics
process equipment or components. Predicting root
Tel: 289-691-0955 causes of failure will save operational costs.
RITZ Automation has experienced people to help you with your information systems
RITZ Automation What Software Tools, Interfaces, Enterprise and Plant Systems are your Other Software Used plus Needs or Comments:
employees using to manage company operations? Any Needs?
What HMI Operator Interface What ERP System Deployed?
Mailing Address Wonderware or WinCC SAP ERP + SQL DB
255 Rankin Blvd Rockwell RSView Oracle EBS, JDE+SQL
Cobourg, ON GE Proficy-Cimplicity MS - Dynamics +MSSQL
Canada K9A 4B8 Name & Company
What MES Tool Do you use? What BI Reporting Tools?
RA FactoryTalk or OPC Hyperion, Oracle BI Email Address
Web www.ritzautomation.ca GE Proficy Solutions Crystal Reports-Bus Obj
Email: lloyd.rietze@yahoo.ca Wonderware ArchestrA OLAP—Datawarehouse Phone

2. THE NEED
The perpetual challenge in the oil-gas, chemical, food, process, steel-metals, mining industries and discrete
manufacturing operations is how to reduce overall MRO/O&M costs while improving overall production?
How many hours of downtime do you incur in your operations annually? What is the cost?
What is 1% of your total operations costs? What percentage are you failing to save?
Areas for Cost impacts include:
* Reduce premature, unexpected, unplanned failures of critical equipment
* Reduce downtime
* Reduce repair, replacement and maintenance expense
Areas for Productivity improvements include:
* Increased availability and uptime
* Improved asset performance
* Improved data utilization
* Better manpower utilization
What’s all the hype around big data? In a recent study, CapGemini reported that leveraging Big Data to
solve business problems will deliver 41% improvement in overall business performance over the next three
years. However, most companies are still struggling to figure out how to leverage this data.
Big Data
"Big Data", the accumulation of many applications and data inputs in the enterprise over the years, has ex-
ploded. In the process based industries such as oil-gas, chemical, food, pharma, mining industry, silo's of
data have been developed including: ERP, EAM, SCM, CMMS, Data Historian, SCADA, and other customized
applications. The ERP integrates most of the various data platforms for common interface but end users are
overwhelmed by the sheer volume of the data and lack the skill set to profitably extract information from
the data.
With the right analytics and the right delivery approach, Big Data flow can power unprecedented asset per-
formance improvement. That's what our solution is designed to do. TI-data uses Predictive Analytics to turn
Big Data flows into actionable information to improve asset performance. We extract relevant critical com-
ponent data from the massive amounts of data flow and then stream actionable information, guidance and
recommendations directly to the end users.

3. This is achieved without major IT or infrastructure impact on your operations. The system delivers
measurable improvement and focuses on the most important highest criticality components.
The system is platform agnostic. We can work with any existing platform and data structure and we
understand how to access the data environment. We create prototypes early and often collaborate with
your end users mitigating the risks of change management.
THE CURRENT ENVIRONMENT
Maintenance Management is not always optimized. Much of it is Calendar based. Much of the condition
based maintenance is based on single purpose sensor data. Some maintenance management is outsourced
to the OEM's or third parties. Data centres are overwhelmed with data and suffer a shortage of technical
personnel. Much of the available data is underutilized.
There is not a comprehensive accurate integration of all cost impacts related to individual component
failures, i.e. repair/replacement costs, production impacts, conditions, availability rates, failure rates, asset
life, capitalization impacts, etc.
Our starting point is understanding the area of greatest need, the highest criticality equipment with an
unacceptably high rate of premature failures.
SOLUTION - EARLY CAUSE DETECTION
Automate and optimize the available existing data to improve critical component availability and overall
asset performance. Implement an early cause detection system capable of enabling remedies to reduce or
eliminate premature, unexpected, unplanned failures of the highest criticality components.
OUTCOMES
The outcome of the Predictive Analytics system projects high returns and major improvements in the
following areas:
Financial Impact
Any failure reversals or eliminations result in measurable reduced costs:
* Direct Repair and replacement costs of labor and materials
* Collateral damage to the equipment system
* Extended asset life of the component
* Other costs related to downtime

4. Equipment Availability Impact
Reversing or eliminating any critical component failures increases availability of the equipment system to perform as
required and, correspondingly, increases production. Ultimately the goal is to eliminate catastrophic failures caused by
critical component failures.
Manpower Impact
Rapidly performing accurate diagnostics of early causes of potential failures provides for:
* Improved accuracy of diagnostics requiring fewer man hours
* Faster response time to potential incidents
* Reduced maintenance backlog
* Faster turnaround time of repair
Asset Performance Impact
* Enables maintaining asset/critical components to peak performance
* Accurate understanding of condition enables efficient use of technician’s time
* Applying remedies at the earliest stages of incidents leading to failure extends the life of the asset
Reliability Impact
By all measurable reliability metrics, reducing/eliminating critical component failure improves overall Reliability KPI's.
Uptime is increased, equipment readiness is improved, downtime is reduced, costs of maintenance, repair,
replacement and total cost of ownership are reduced.
Overall Outcomes:
* Accurate metrics proving, calculating the value and financial impact of the targeted critical components
* Eliminate/Reduce catastrophic failures
* Eliminate/Reduce premature failures
* Eliminate/Reduce unplanned/unexpected failures
* Reduce repair and replacement costs
* Reduce downtime
* Increase availability
* Improve performance, productivity outputs
* Extend asset life
* Financial value opportunities - metrics to combine several or all of above to calculate value of the component save
and the investment ROI of the “Predictive Analytics System”
……...Next More Detailed Examples of our systems pages 5-6

5. Your business decisions have the power to propel growth by using RA’s data-driven software technology solutions.
This allows you to visualize, analyze, and optimize production & process data across your enterprise operations.
RITZ Automation will provide you with a custom solution that meets all of your business goals, objectives and
operational excellence which will address these issues:
1. Increase quality of parts–batches-processes by real time review of production or processes, and event monitoring
all production-process-equipment control data, upper and lower control limits, set points, recipe - formula data, and
critical components
2. Minimize downtime & costs by event linkage of equipment data to maintenance mgt systems reduces costs thru
scheduled and event analysis linking equipment faults with repair work orders, parts, and staff.
The PREDICTIVE ANALYTICAL Management Systems (PAMS) uses models based upon root causes for failure of all
critical production-process equipment. It can predict unplanned, unexpected and premature failures of components
saving you substantial MRO costs and reduction of productivity and downtimes. Conventional CMMS and MES
systems do not have the ability to determine and detect root causes of failure. PAMS provides analysis of what caused
premature failure and then notify operations/maintenance in advance that these conditions will happen soon and it
now time to take ACTION before failure. Conditioned Based Monitoring (CBM) is only a part of the analytical aspects
of PAMS.
3. Quantitative-Qualitative production-process analysis achieve business objectives (lower costs, better quality etc)
4. Use OEE-SPC analysis metrics and controls data from automation devices PLC-PACs, sensors, smart meters, pumps,
valves, drives, DCS, electrical control panels, energy mgt systems, HMI-Operator interfaces, instrumentation devices,
etc.
5. This allows for major savings by gathering Government Compliance data for Safety, Environmental, FDA-CIFA, 21
CFR Part11, ISO Standards, HACCP for Food Industry, SOX Compliance in USA, collection and reporting issues
streamlined
6. By gathering and reporting process and production data, employees will make better decisions and save operational
costs by watching critical control points and sensor data watching variables such as temperatures, pressures, flow
rates, speeds, moisture levels, vibration, voltage, current, amps, frequencies, and other condition alarms on
equipment.
Use this data for predictive analysis (see below and BIG DATA PAMS section) and links to CMMS (computerized
maintenance mgt systems) to replace production and process equipment components before they fail.
An Intelligent Approach
The objectives of condition-based maintenance are:
1. preventing unplanned downtime
2. making better use of maintenance resources
3. maximizing the operational life of your assets
A condition-based maintenance program takes real-time asset data and gives it the predictive power to add capacity,
reliability, and profitability to your operation.

6. Predictive Analytical Maintenance System (PAMS)
Imagine being one step ahead of breakdowns, avoiding failures, and efficiently planning and scheduling maintenance.
You can automate preventative maintenance and remove the need to manually collect readings and enter results into
computerized maintenance management systems (CMMS).
Traditional maintenance is based on asset run-hours, cycle times, equipment starts/stops, process data like
temperatures, pressures, flow rates, chemical data, high-low parameters, and mechanical-electrical information
sourced directly from plant floor or process or other assets like vehicles or field equipment data and fed automatically
into your CMMS to drive your asset’s maintenance schedule.
Cut Costs with Predictive Maintenance
PAMS is not a product but a custom designed managed service. We work with your people to design, analyze data
using AI and mathematical models and deploy results to your other management systems. We design cost effective
PILOT projects on the top key components of your business and then develop models for your other major
components. Our SaaS - Cloud servers and PAMS system is then charged back on a monthly fee based plan. Our
system is viewed through your internet browser and we pass along data into your systems of choice for use.
Predictive maintenance techniques determine the condition of your in-service equipment to predict when
maintenance should be performed. This approach saves you costs compared to routine or time-based preventative
maintenance because tasks are performed only when needed.
Predictive Analysis Maintenance techniques enable you to:
1. Capture the intellectual property for the specific condition assessment
2. Leverage information from your CMMS and online plant data
3. Monitor distributed assets centrally
4. Predictive Action reporting to maintenance and
5. Display asset condition on a digital dashboard
6. Predict failures before they happen based on early premature causes & estimate days to failure, order parts, replace parts
7. Be alerted to issues due to maintenance practice failures, monitor SOPs and update methods to prevent future mistakes
Beyond Condition Based Monitoring and CMMS
The four stages of failure —Determine analytical root cause and effects of components before they fail:
Stage 1 - Early incidents of Cause
Stage 2 - Effects of early cause impacting the component
Stage 3 - Potential for failure is detected, remaining useful is calculated, repair and replacement plans are implemented
Stage 4 - Functional Failure - the component ceases to perform
We design systems for Stage 1 and 2 and link this data into existing CMB, CMMS, Asset Mgt and ERP systems. We
design user friendly Action Reporting for both real time and predictive maintenance management. Replacing
components before they fail but extending the life before the end of its life cycle.
Predictive Analytics greatly improves the performance of mobile and remote capital-intensive operations that are
complex and multi-faceted. Predictive Analytics interprets the interrelationships of complex multi-dimensional factors
using historical and near real-time data. Based on Artificial Intelligence, the models' accuracy and sensitivity better
defines and predicts normal operations, and detects abnormal operations at a much earlier stage.
By predicting failures before they happen and then link into CMMS/SCM to determine optimum maintenance
planning, purchasing, scheduling, and supplier component replacements, your operations save substantial operational
downtime costs and increase profitability.