The Importance of Plant-level Systems
Written By: Predrag Jakovljevic
Published On: November 21 2005
Currently, there are industry-wide concerns about the lack of consensus to define standards for connectivity and interoperability between various plant automation, manufacturing execution, and enterprise level systems. The upsurge of interest in standards-based interoperability indicates that manufacturers need better options to connect business processes throughout the organization.
Investments made in systems managing production processes in plants and within entire supply chains are playing a larger role and gaining in value as companies move toward using data collaboratively to support business processes. Originally, companies acquired plant systems to support narrow functional requirements, such as production order tracking, quality assurance (QA), time and attendance tracking, warehouse management, laboratory systems, production scheduling and sequencing, or plant and equipment maintenance and repair depot management. However, in the "New Economy" where an environment of increased collaboration, information sharing, real time business, and burgeoning compliance requirements exists, the place and value of plant-level systems in the corporate information technology (IT) portfolio hierarchy has become more significant.
Plant-level execution systems have largely been ignored and taken for granted, although they are vital for effective shop floor management and give first-line supervision staff visibility to manage work orders and work center assignments. Compared to enterprise applications like enterprise resource planning (ERP), customer relationship management (CRM), or supply chain management (SCM) systems, which traditionally run in a batch mode and on a planned basis (with operating cycles of weeks or more), IT department, financial managers, planners, and other white collar staff have often treated production support needs such as manufacturing execution systems (MES), QA and lab systems, plant maintenance or warehouse management applications, as a necessary evil.
Although needed and cherished by department managers, most plant level systems have been difficult to justify. Plant-level systems are online transaction process-based (OLTP) and operate in seconds and minutes. Their transaction frequency is far shorter than typical enterprise applications and usually fall "below the radar" of most corporate IT decision makers.
Nevertheless, times and attitudes are changing, as user enterprises are increasingly asking about shop floor integration with the back-office. They want these systems to "talk to each other", and many customers are adding integration their requirements lists. The IT environment in manufacturing is facing a dramatic change, and traditional systems characterized by a standalone, static business model requiring periodic manual data entry, and sequential transaction processing have to evolve into systems that support near real time, collaborative business models. The purpose of this shift is to make product supply predictable, lower inventory levels, and created better response to demand. Other foreseeable benefits include reduced variability, improved compliance, decreased cycle time, and so on.
Visibility into operational measurements also provides the foundation for ongoing process improvement and can be an important enabler for Six Sigma, a set of concepts and practices that reduce process variability and deficiencies in a product; and balanced scorecard, a list of financial and operational measurements used to evaluate organizational or supply chain performance, which formally connects overall corporate objectives, strategies, and measurements. For more information, see Why Most Balanced Scorecards are Subverted). In these emerging business models, the entire business ecosystem is connected in a network. New real time management methodologies based on synchronized business processes, real time decision support, management by exception, performance-based service level agreements (SLA), and the like are used to drive manufacturing performance to the next level.
This is Part One of a three-part note. Part Two will discuss the obstacles to overcome and current developments. Part Three will analyze the market impact and make user recommendations.
What Manufacturing Now Values
Nowadays, manufacturing organizations are placing a much higher value on the information generated, aggregated, and used by events and processes within real production and logistics worlds. Information on labor, inventory measures, lead times, maintenance and operational equipment effectiveness (OEE), product data accuracy, uptimes, utilization, bottlenecks, yield/scrap metrics, etc. is valuable in environments where operating in near real time is critical. For instance, as SAP planned its 2005 delivery of Manufacturing Dashboard, it reportedly talked to over forty plant managers and over one hundred production supervisors, and asked them flatly "What do you do during the day to fulfill your role?" and "What do you need to be made more productive?". SAP reportedly found that this group needed a collection of consolidated information from a variety of sources and applications, and detailed knowledge of what is going on in the real world. Through these discussions, the vendor recognized that a portal might provide the ability to bring information together technically, but many gaps still need to be filled to meet customer satisfaction.
Supply chain planning and execution (SCPE) concepts have been used long enough to make a real difference, and more companies are making progress and taking excess, unneeded inventories out of the system. In other words, the amount of inventory available to cover uncertainties in the complex, multi-echelon supply chain is decreasing continuously, leading to the need to react quickly.
One should not forget that there are other areas to tap into that can make a business more agile, such as shop floor applications (see The Why of Data Collection). Thus, management is increasingly using business processes to strive toward greater information sharing and collaboration. Enterprises are addressing broader, real time business issues through initiatives such as analytics, business intelligence (BI), business activity monitoring (BAM), enterprise performance management (EPM), digital dashboards, supply chain event management (SCEM), collaborative product lifecycle management (PLM), mobile devices, radio frequency identification (RFID) etc. to create a real time enterprise (see Attaining Real Time, On-demand Information Data: Contemporary Business Intelligence Tools).
All of these initiatives center on the idea of near real time information sharing and use, preferably from its originating source. In practice, operating an adaptive enterprise requires real world awareness, which means providing timely information and establishing business processes that bridge traditional application gaps.
Many newer business initiatives, including collaborative manufacturing strategy applications, require near real time information to be available in order to satisfy even simple needs. The strategy of synchronizing inventories and production across a supply network requires knowing the current status of events, what is happening at a particular moment, what is expected, etc. It is insufficient to have a report of what happened last week or even yesterday. To be truly "in sync" requires timely information from plant- or warehouse- level processes, not a "guesstimate" about what was scheduled or what should have happened.
Some avant-garde user companies are leveraging business process management (BPM) tools to retrieve information from disparate sources, redefine data context and logic, and provide aggregated data in other systems (see Business Process Management: How to Orchestrate Your Business).
Some BPM vendors provide a connection capability designed specifically as a BPM tool to implement process logic between new and legacy plant-level software components. One example of this is linking QA data to an SCEM system to monitor production yield information, and then broadcast results to user constituencies. An additional step might include providing that data to the planning and scheduling system in near real time for automatic optimized rescheduling. A company, for example, could inform downstream supply chain partners of the QA data, the resulting yield, the revised schedule, and of current shipment information as the information is developed in the transportation management system (TMS).
This concludes Part One of a three-part note. Part Two will discuss the obstacles to overcome and current developments. Part Three will analyze the market impact and make user recommendations.