The Increasing Value of MES and Plant Process Information

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About the Author

Michael McClellan has over 30 years of experience serving and managing manufacturing enterprises. He has held a number of positions in general management, marketingand engineering, including President and CEO for a multi-division equipment systems supplier.In 1984 he and a group of associates founded Integrated Production Systems, a company thatpioneered the use of computer systems to manage and track production events on the plant floor. His first book, Applying Manufacturing Execution Systems , defines manufacturing execution systems and explains the reasoning and history behind them. He is a frequent speaker at companies and manufacturing conferences, has presented a number of papers on plant information systems, and holds one patent. He has recently completed a new book, CollaborativeManufacturing: Using Real-time Information to Support the Supply Chain.

He currently lives in Washington state and is President of Collaboration Synergies Inc. , anadvisory company providing consulting services in the areas of business process management, collaborative manufacturing system development and implementation, plant floor information systems and manufacturing execution systems.

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The investments made in production process and value chain systems are playing a larger role and gaining in value as companies move toward collaborative uses of data to support core business processes. Originally these systems were acquired to support narrow functional requirements such as production order tracking, quality assurance, warehouse management, or maintenancemanagement but in the new environment of collaboration, information sharing, real-time business,and broader compliance requirements, their place and value in the corporate IT portfolio hierarchyis increasingly significant.

Gaining Respect

M a n u facturing systems have long played the Ro d n ey Dangerfield role – a role where they could not geta ny respect. Compared to the enterprise re q u i rements planning (ERP) system or the customer re q u i re-ments management (CRM) applications or even supply chain management (SCM), production supportneeds such as manufacturing execution systems or wa rehouse management applications we re fre q u e n t l yt re ated as unwa n ted step children. Though needed, loved, and prote c ted by departmental managers, mostplant systems have been difficult to just i fy on the basis of reduced costs and usually fall below the ra d a rof corporate info r m ation technology managers. But the times are changing. Th e re is now much highervalue being placed on the info r m ation detail that is generated and used by events and processes withinthe production and logistics world. This is where the value-adding action is in a manufacturing company,and as businesses move closer to operating in a near real-time env i ronment, reports that are re c o rds ofye ste rd ays events are simply too late or do not have enough detail to support eve r yd ay business decisions.In the sense-and-react env i ronment of modern businesses, it is the data generated as events are occurringt h at provide the best basis for management decisions and actions.

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The Manufacturing System

It is difficult to easily identify or define the full range of applications used to accomplish pro d u c t i o nbecause industries are diffe rent and vendors have never hesitated to add to the confusion by using labeling to suggest diffe rences. The broad definition begins with a holistic view that includes the completep roduction system infra st r u c t u re, the collection of business processes that provide the eve n t - by - eve n treal-time management and execution of the planned production re q u i rements. But even that is not ana d e q u ate definition until we include each enterprise in the value chain on both the supplier side and on the demand side.

In an individual plant there could easily be 40 or more applications generating info r m ation or contro l l i n gm a n u facturing processes. In this illust ration many of the typical plant processes are shown. Although theterm has wide meanings, for purposes of this article I will describe the collection of these applications asthe manufacturing execution system (MES) and/or the enterprise production syste m .

L i fe would be easy if the plant processes we re as simple as this illust ration suggests. Unfo r t u n ate l y, re a l i tyis a bit messier with plants typically running 20 to 40 diffe rent applications that have been installed over the past 10 or more years. Within a multi-plant company or within a supply chain, the number ofa p p l i c ations can grow to hundreds of disparate data generators and info r m ation sources. The value ofthese applications has been typically based on each system as a stand-alone answer to a particular set ofo p e ration conditions. The aggre g ate value of the manufacturing execution system is not considere dbecause business tends to think of these applications in a data-centric view.

WORKORDERS WORK

STATIONS

EXCEPTIONS

DATACOLLECTION

MATERIALMOVEMENT

ERPINTERFACE

INVENTORY

LIMS

SPC

WAREHOUSESYSEM

TIME &AT T E N DA N C E

M A I N T E N A N C E

DOCUMENTS

GENEALOGY

SUPPLIERS

END OF LIFE R E G U L ATO RYC O M P L I A N C E

SCHEDULING

QUALITYASSURANCE

LOGISTICSMES

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Data-centric View

The data centric view is narrow and focuses on the original re q u i rements to support a specific pro c e s scausing the functionality to be designed and built with a very inwa rd sense. As an example consider an application designed to support the quality assurance department. Although important quality management issues such as st at i stical process control, non-conformance measurement and st at i stics, c o r re c t i ve action support, in process te st, and more, are usually included, ra rely will the package addre s sor have any connection to equally important issues such as WIP tracking, cost variance, or scheduling.Early material re q u i rements planning (MRP) systems we re of ten described as closed loop systems. Th eo p e rator ente red data, the sof twa re did the calculation, and clear truth emerged. It was indeed a closedloop that focused on internal mechanisms (pure logic unadulte rated by outside fo rces) to deliver ana n swe r. This inwa rd focus towa rd a narrowly identified list of departmental functions is what drives the frequent re fe rence to many plant systems as islands of info r m ation. A much gre ater value can be e nvisioned when we alter our thinking away from the data-centric view to a process-centric view.

CRM

QA

SPC APS

ERPWMS

LIMS MES

A p p l i c ations Are Inwa rd Oriente d

Legacy Applications Are Hard to Re a c h

D ata-centric Wo r l dLogic Was Not Designed for External Use

No Compet i t i ve Ad va n t a g e

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Shifting to Collaboration

Th e re is a major shift occurring in the use of this info r m ation from the historical use of managing a plantfloor department or function to a much broader role of providing real-time info r m ation necessary to manage the enterprise business processes and support collaborat i ve initiat i ves across the value chain. In life science industries process applications provide FDA re g u l atory compliance confirmation i n fo r m ation. In discrete item industries, the primary source for product genealogy info r m ation includingcomponent sourcing, quality assurance confirmation, and product run-in te st data resides in process a p p l i c ations. Meaningful key performance indicators and business performance management initiat i ve sa re likely to re q u i re the key data items that are found in the production system and available in near real-time.

Business management is increasingly using a business process focus as we drive towa rd gre ater p a r t i c i p ation in info r m ation sharing and collaboration. Broader real-time business issues are being addressed through initiat i ves such as analytics, business activity monito r i n g /management, businessp rocess intelligence, business performance management, digital dashboards, supply chain event management, collaborat i ve value chains, product life c ycle management, the real-time enterprise, and so on. The list continues but all of these initiat i ves center on the idea of real-time info r m ation sharing and use, pre fe rably from its originating source. In the typical value chain, that source is usually the m a n u facturing execution systems within the business unit and/or value chain partners.

The value of the info r m ation changes when used to support higher level business processes. The data hasone value when generated for a department supervisor for management purposes and quite anot h e rvalue when the data is also used to meet Sarba n e s /O x l ey compliance needs. Another example is how thevalue of quality assurance info r m ation increases substantially when used to support enterprise wide wa r ra n ty ex p o s u re issues. Inve n tory info r m ation takes on a diffe rent look when viewed across a va l u echain with sy n c h ro n i zed schedules based on real demand. This gre ater value comes by changing f rom a data-centric view of manufacturing applications to a process-centric view of the how higherimpact company processes can be supporte d .

Defining Collaborat i ve Manufa c t u r i n gSimultaneous use of real-time info r m ation across the value chain

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Business Processes

M a ny newer business initiat i ves, including applications of collaborat i ve manufacturing st rategies, re q u i renear real-time info r m ation ava i l a b i l i ty to sat i sfy even simple needs. The st rategy of sy n c h ronizing i nve n tories and production across a value chain re q u i res knowing the current st atus of events, what isoccurring at this moment, what is ex p e c ted, and so on. It is not enough to have a report of what happened last week or even ye ste rd ay. To be “in sync” re q u i res current knowledge from the pro c e s s e st h e m s e l ves – not an assumption of what was scheduled or what should have happened. Other forms of sy n c h ro n i zed production including lean manufacturing and demand-driven manufacturing are based on manufacturing to actual demand in an online env i ronment, completing the management info r m at i o nloop with process data that confirms compliance with value chain objectives. The ideas behind these management concepts are based on near real-time inte raction of confirming info r m ation among va l u echain partners using the full array of production system components as intelligent info r m ation sources.

Product life c ycle management can include data from product design through end-of - l i fe processes. M a ny of the components of PLM are supported by data that originates during the manufacturing p rocess and is sto red in production applications. Product genealogy info r m ation such as te st results, q u a l i ty assurance data, and component source info r m ation are a few examples.

Product Life-cycle Managementrepresentative steps in a value chain product lifecycle

I n t ra - C o m p a ny Collaborat i o nAccounting • Manufacturing • QualityPu rchasing • Compliance • Lo g i st i c sM a r ket i n g /Sales • Pa c ka g i n g

Product Improve m e n t s

Pro d u c tD e s i g n

E n g i n e e r i n g

Pro d u c tC o n c e pt

E n g i n e e r i n g

S e r v i c eRe c o rd

D e l i ve r yto

C u sto m e r

End of Life Pro c e s s e s C u stomer Comments

Value Chain Collaborat i o nC u stomers • Distribution • Suppliers

Collaboration Environmentand Information/Data Storage

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Data Sources

The hard part about incorporating production data into wider use is the problem of ret r i eving the specificre q u i red data and arranging the data in a context that supports a business process. Histo r i c a l l y, this has been very difficult. Most info r m ation technology departments are not closely connected to plant o p e rations or various MES components and have very little awa reness of what data is available or h ow to ret r i eve it. A medium-sized fa c i l i ty could have sixty or more disparate components within theirMES. Many of these applications very likely we re built to specifications long since fo rg ot ten using technology that is no longer current. Documentation is frequently poor or nonex i stent. Further, when thed e s i red info r m ation has been determined and located, the cost and time to inte g rate the data sources onthe plant floor have been pro h i b i t i ve.

M a ny vendors are improving data accessibility in diffe rent ways. Many are moving to broaden their p roduct/function fo otprint. Most have perc e i ved the necessity of including a wider range of info r m ation in their systems, of ten with a particular emphasis on quality assurance, product life c ycle, and genealogyi n fo r m ation. Other vendors are building exte n s i ve product of ferings through acquisition, with the a p p a rent plan to inte g rate this functionality into modular product suites. Th e re are a few companies t h at are providing a fully inte g rated MES that includes modules for wa rehouse management, scheduling,p roduct data management, process modules, maintenance and repair, quality management, and web services.

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The Process Layer

One other idea gaining in popularity is the inclusion of a process layer that can easily link to data sourc e s ,ret r i eve specific data, perform process logic, and deliver an output. Manufacturing intelligence systems assupplied by Lighthammer Sof twa re are being applied in many industries to bring appro p r i ate info r m at i o ni n to context for pre s e n t ation and analysis.

These systems have the ability to ext ract real-time process info r m ation from plant-focused sources, a g g re g ate the data from dissimilar sources into a meaningful context, and provide actionable inte l l i g e n c e .Th e re is also a gre atly expanded use of business process management (BPM) tools to ret r i eve info r m at i o nf rom disparate sources, redefine data context and logic, and provide aggre g ated data in other syste m s .One supplier includes a linkage capability that has been designed specifically as a business process management tool to implement process logic between new and legacy MES components. One example of this is to link quality assurance data with a supply chain event management system to monitor yield info r m ation and bro a d c a st results to internal users. An additional step might be to provide that d ata to the planning and scheduling system in real-time for auto m atic rescheduling. To extend this further, we might inform dow n st ream value chain partners of the quality assurance data, the resulting yield, the revised schedule, and current shipment info r m ation as developed in the logistics management system.

The change in manufacturing companies to collaborate more closely and to move towa rd a re a l - t i m ei n fo r m ation paradigm is revising the value proposition of MES. In previous times, applications we re typically narrow in scope, thus making ret u r n - o n - i nve stment just i f i c ation difficult. In to m o r row ’sm a n u facturing enterprise, MES intelligence will more directly support enterprise and value chain o b j e c t i ves aimed at inve n tory management, improved customer service, shorter process cycle times, true compet i t i ve advantages, improved prof i t a b i l i ty, and wider st a keholder success. Support for thesehigher level business processes is providing a new role for MES as a major source of enterprise i n telligence, driving their current renaissance.

Collaboration Synergies Inc.P.O.Box 871555

Vancouver, WA 98687

360.833.8400

www.cosyninc.com