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Three Global Manufacturing Imperatives

In addition to the traditional issues ofproducing and shipping products, todays

manufacturers are facing a new set ofchallenges, pressed upon them by theirrespective positions in the globaleconomy. How they respond to these willlikely determine their success or failureinto the future.

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As Thomas L. Friedman explains in his bookThe World Is Flat, ever-accelerating advances

in technology and communication have shrunk the world to the point where up-and-coming

economies now challenge the developed world to run even faster just to stay in place.

Nowhere is this more evident than in the manufacturing sector, where the rate at which the

issues are changing is accelerating. In addition to all that they had to address in the past,

now companies must also respond to at least three significant new global imperatives:

Global environmental awareness rising cost of energy and the environmentalimpact

Ever-increasing need to be more agile customer demand is driving theeconomic order quantity to one

Response to competition in a global economyManufacturers who are unable or unwilling to address these drivers are unlikely to survive

in the long term. Fundamentally, these are information problems, not equipment or people

or process issues. The solutions must integrate with existing manufacturing and enterprise

business systems not replace or ignore them for these are the primary sources of the

data that ultimately drive the solutions.

Environmental Awareness

These are notmanufacturingproblems. Theyare, in fact,manufacturinginformationproblems.

The first driver is greater awareness of global environment change and the fact that

manufacturers themselves are a major instigator of the problem, more so even than the

automobile. In the aggregate, global manufacturing consumes more than 60 percent of the

worlds energy, produces 75-80 percent of the worlds emissions (not counting automobiles)

and creates more than 90 percent of the worlds hazardous materials.

The high costs of energy, global warming and waste are issues manufacturers can no

longer ignore. They must change the way they do business because the world is now

watching. Customers, shareholders and regulatory agencies are all taking active positions

on these topics, forcing business to show evidence of legitimate action to resolve them.

They must use less energy and minimize the emissions and waste they generate. Above

all, they must show they are actively getting better, not worse.

While these are all issues affecting manufacturers, they are not manufacturing problems.

They are, in fact, manufacturing information problems. Major manufacturers are now

naming senior executives to manage efficiency, energy or clean tech chief sustainability

officers, for example, whose responsibilities are to address these issues company-wide.

Agility

Agility is at first glance a supply chain issue, driven by mounting consumer expectations for

rapid turnaround of product with custom features a make-to-order product demand. For

a manufacturer to be agile requires information transparency throughout the organization,

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end-to-end and top-to-bottom, with a commitment to employee empowerment and a bias

for action, all based on an increasing appetite for better, timelier information.

So where does this information come from? Interestingly enough, the requisite information

is a hidden asset buried among the data accumulating along the dynamic supply chain,

including the many systems in manufacturing and at the business level.

These data are in systems that account for all aspects and states of inventories, including

those managed by the various vendors supplying the manufacturing operation. They are in

order processing systems; in asset utilization, production control and quality assessment; in

energy management, including predictive algorithms and historical behavior of plants and

equipment; in the coherent and timely analyses of production schedules and capacities of

plants and facilities around the world. And so many more literally hundreds of disparate

systems in a large global manufacturer.

One can only imagine what it would be like to gather data from all of these systems, to

integrate and correlate it, to overlay specific business context, and to extract timely,

meaningful information from it. In the future, the extent to which a company is able do this

will determine the degree of agility that company can achieve. And the future is now.

Enhancing Competitiveness

The value ofcontinuousimprovement isenormous.

How do you win the global competition? Easy. Be a smarter manufacturer. Commit to a

process of continuous improvement on all fronts. Be more responsive to customer demand

and quicker to market with a more creative and flexible design. Reduce manufacturing lot

sizes and customize to specific customer requirements. Make products more cost-

effectively. Be more adaptive in leveraging production automation. Eliminate production

waste and turn inventories five-to-ten times faster. Consistently produce higher quality

products, with higher yields. Maximize asset utilization. Overcome high transportation costs

by optimizing sources of supply and manufacture specific products as close to the customeras possible. Easy right?

In the end, the value of singular improvement in any one of these areas is marginal. But the

value of continuous improvement across all of them is enormous. As with the previous two

imperatives, this is an information problem. In this sense, real competitiveness is the ability

to optimize across business and production processes. It is a matter of providing timely

business intelligence for the entire company, not just the IT department, and not just in the

form of end-of-period reporting.

By resolving these information issues using todays service-oriented architectures (SOA) to

overlay business intelligence (BI) on manufacturing or whats now becoming known as

enterprise manufacturing intelligence (EMI) producers can respond far more effectively tothese and any new business drivers.

Changing View of Business Intelligence

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Business intelligence is not a new concept, but it has evolved to a new form in the last five

years. Classical BI was originally an IT tool designed to perform heavy-duty data analysis

based on results stored in business systems. It facilitated high value business decisions

that affected the long-term business strategy. It was initially aimed at macro level decision-

making, to collect the data, extract it, purge it, and then slice and dice it in multiple ways for

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use by the right people. Users would debate the answer and finally implement the solution.

The principles and tools embodied in BI solutions were designed for and only applicable to

enterprise-level systems.

Today's enterprise manufacturing intelligence is aimed at micro level decision-making, at or

near real-time speeds. To quote Bill Gates it is business at the speed of the internet.

Its designed for use with plant operations in a business context provided by enterprise

systems and therefore deals with small, incremental changes that affect todays work

right now, as it occurs. The intent is that, over time, effectively made smaller decisions will

roll up and yield big results. This presents a very different scenario of common wisdom in

the manufacturing world.

The key components of business intelligence for manufacturing/EMI are:

Ability to connect to virtually any data source in the enterprise Plant floor production systems for automation and control

Having thebusinessinformationreadily availableempowerspeople to makeoptimaldecisions in real

time.

Enterprise business applications that provide business context Capability to aggregate data from those multiple disparate systems

Put data into proper context for individual users (to transform data intoinformation)

Provide analysis tools to trend, aggregate, correlate and report thatinformation

Ability to web publish information for use by others View key performance indicators (KPIs) and dashboards, trends and

reports through company-wide portals, using ordinary web browsers

Use familiar tools for interacting with data (such as Microsoft Excel)A Practical Example

If an important piece of equipment breaks down or shows signs that it is on the verge of a

breakdown, what happens? Typically the organization falls back on its collective experience

and views the production cost of the equipment being down in terms of dollars per hour.

This experience tells production that it must react quickly because it is costing tens or

hundreds of thousands of dollars an hour while the equipment is offline. This approach is

invariably based on the assumption that having machinery and equipment down is a bad

thing, and that getting it back up and running as soon as possible is a good thing, no matter

what the cost.

However, if there were time and appropriate tools for analysis of a multiplicity of details, the

situation may indicate another reality.

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If the equipment was nearing the end of a full production cycle or was due for routine

maintenance anyway, and if staff and spare parts were known to be at hand, it might in fact

be lower cost and more efficient to proceed with the repairs. However, if there is timely

access to the appropriate data there may be other factors that could and should be

considered. What is the current level of inventory vs. short-term demand for the product

made on the machinery, calculated by the hour or shift? What is the real revenue impact of

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not getting the equipment back up immediately? Is there another production line running at

less than full capacity that can pick up the slack and allow for service to the equipment? Is

there another plant producing, or capable of producing, the product to meet the demand

and what is the cost of temporarily transferring production there, including shipping? Are

the appropriate resources (parts and maintenance staff) available to perform the required

service, or would parts need to be ordered and/or staff need to be paid overtime?

Typically, these questions are never asked because there is never time or resources at

hand to gather the data and do the analysis, so organizations resort to the book that says

to get the equipment back on line immediately. Having the business information readily

available to answer these and more questions empowers people to make optimal decisions

in real time.

Enterprise manufacturing intelligence provides management and line personnel access to

this data and the tools with which to analyze the current situation when problems occur. It

enables users to drill into production and maintenance data, in the context of the current

business situation, to quantify relative costs of alternative response scenarios. It provides

these tools on-site via thin client Internet or intranet access. It does not require that lots ofdata be collected and taken back to the office for analysis by the experts the work is done

where the problems manifest and people are empowered to make profitable decisions in

real time.

Lets consider some real-world examples.

EMI Increases Productivity in the Paint Industry

The worlds oldest paint company uses EMI to significantly increase productivity to the

point where it now makes more paint in two shifts per day than it had previously made in

three. Using the FactoryTalk VantagePoint (previously named IncuityEMI) software, they

have been able to drill into their processes to examine differences in cleaning cycle timesfor different batches of products, then adjust the production schedules to optimize multiple

cycle operations. They now run more similar products before switching to others, effectively

creating longer, less costly production cycles in place of short, higher cost production

cycles. This had not been taken into account before even though the data was readily

available they simply didnt have the wherewithal to see it in the business context. Now

these production decisions are made in real time because the information is readily

available through web-based dashboards and KPIs.

They also now do a much better job of coordinating the end-to-end production process,

including coordinating paint batches with can filling lines to better schedule filling operations

and eliminate wait times for new products. This enables more efficient changeovers of

products and categories and they now have increased production by more than 30 percent

which amounts to a savings of $500,000 per year. Now as demand grows they have the

capacity to grow with it, with the potential further savings of delaying the need to deploy

new plant and equipment by adding back a third shift.

EMI in Pharmaceuticals

A pharmaceutical company uses EMI to improve energy cost assignment to actual

production. Sophisticated production equipment (extruders, rollers, strippers, packagers)

consumed high volumes of electrical power, but energy costs were allocated to the various

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aspects of production within their ERP system, not their production systems. This meant

there was no incentive for production managers to use power more efficiently. The data

existed in various systems in production, but the time and effort to extract the consumption

details and analyze it in order to empower managers and production workers to conserve

seemed out of reach. The production lines in question therefore were not profitable and

they suspected that energy was a major contributor, but did not realize the magnitude orany concept of how to address it. They were considering closing down the business unit.

Adding the capabilities of FactoryTalk VantagePoint business intelligence software meant

they could drill into production control systems to gather real-time energy usage data in the

context of specific production runs and specific equipment, then analyze it and upload the

result back into the ERP system. True cost allocation has driven a savings of nearly

$200,000 a month, and the production line changed from being a significant loss generator

to a smoothly functioning profit center, preventing the potential closure of the business unit

in question.

EMI in Specialty Chemicals

This provides avalue-addedcurrency foreach step of acompanysoperations sothat everyworker knowsthe true costimpact for eachbusinessdecision.

Another example is a specialty chemicals producer that used EMI to optimize processes by

eliminating idle time in batch production. The plant was making an intermediate chemical

product, orders for which exceeded their ability to produce. As a sold-out product, if they

could make more, they could sell more.

Everything seemed to be running right, but intuitively they knew they could do a better job.

There was a solution buried in the data, but they were unable to ferret out any meaningful

solution. It turned out that batches were running properly but there were wide variations in

idle times for making different batches of the same product on multiple production lines.

Using FactoryTalk VantagePoint dashboards and web-based analytics, staff personnel

were able to drill into operating detail and discovered anomalies that caused the variations.

In one example of many, a manual vent-down step varied widely when operators were

busy, so the entire process idled while they finished other tasks. With real data, workers

were able to do a true cost-benefit analysis of replacing that manual valve with an

automated one, so the process no longer waited for operators. Output increased, as did

sales.

As another example, some of the batch heat phases took longer to complete than others

did, but they could not determine why. Using FactoryTalk VantagePoint, they correlated

disparate production line data with data on steam temperatures in their utilities department

and discovered a wide variation in the actual steam temperature supplied to production

lines. At times, the steam simply was not hot enough, so they put the appropriate controls

in place and ordered super-heated steam from the utilities department. This considerablyshortening the batch heat times and the result was improved output on the initial production

line by approximately 5 percent. They now are instituting similar projects on other lines and

at other plants.

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Publication FTALK-WP015A-EN-E March 2009 Copyright 2009 Rockwell Automation, Inc. All Rights Reserved.

Creating KPI Currency

Enterprise manufacturing intelligence offers companies a powerful new weapon in the battle to

manage the core business drivers for industry. The ultimate use of EMI is to access the data

buried in various systems in operations, apply a business context to it and roll it up into a

single common denominator financial impact.It allows management and informed workers at all levels of a company to view real-time KPIs

and dashboards and, when problems occur, to drill down into the root causes and resolve

them before they manifest negative financial results. EMI allows companies to similarly

aggregate information across multiple production lines and plants and provide a global

financial perspective when problems arise, empowering people to prioritize and address the

ones that produce the greatest return.

This provides a value-added currency for each step of a companys operations so that every

worker knows the true cost impact for each business decision, at the time the decision needs

to be made, every step of the way. This underscores the major difference between EMI and

traditional BI tools: EMI is a powerful, dynamic, in-process decision support tool. BI is a statictool that reports on results, after the fact.

This new context provides a holistic view of operations, empowering continuous performance

improvement over time. EMI drives the alignment of operations with current business goals,

empowering informed line personnel and management with the tools they need to determine

the cost impact and profitability of every decision.

For more information on FactoryTalk VantagePoint, visit discover.rockwellautomation.com to

view a brief video on FactoryTalk VantagePoint and to view other information that describeshow this software can improve your companys bottom line.

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