GE Intelligent Platforms. Resource Intensity The Metric That Links Operational and Sustainability Goals

Transcription

1 GE Intelligent Platforms Resource Intensity The Metric That Links Operational and Sustainability Goals

2 Resource Intensity The Metric That Links Operational and Sustainability Goals Introduction As manufacturing sustainability leaders seek to drive changes in their company s products, processes, and utility infrastructure, the lack of established sustainability measurements can make it challenging to communicate the relevance of stewardship goals to operational goals. While other disciplines such as finance and operations have evolved rich metrics schemes over time, sustainability is still evolving in both its practices and its measurements; so there is no common language that eases communications between stakeholders when discussing ways to mitigate environmental impact. The terms and measures that are most commonly discussed in the media focus on carbon footprint, carbon accounting, cap and trade markets, and the like, and that leads to a sense that somehow sustainability in general is in some ways detached from the tangible facilities and operations of producers. Discussion is further clouded by the fact that external parties governments, retailers, and a concerned public can cast goals too starkly, leaving little room for informed debate. The disdain shown in the public and the media for intensity measures of water, carbon or energy is a good example of how the lack of a mature set of metrics and common practices in using those metrics to communicate can lead to important reduction goals being obscured. Drawing from long experience assisting producers with their efforts to make operational improvements, GE Intelligent Platforms is able to draw parallels between the development of continuous improvement approaches such as Lean or Six Sigma and the evolution of sustainability improvement initiatives. This paper demonstrates how the measurement systems and Key Performance Indicators (KPIs) that evolved alongside operational improvement practices offer much of the structure needed to properly link sustainability goals to overall operational and cost-improvement goals. Good Metrics Have Scope and Scale Looking at metrics used in production operations and finance, they have several key elements in common: 1. Different views of data can be made at very aggregate levels (e.g., Profit & Loss in finance; Overall Equipment Effectiveness in production), at very granular levels (e.g., journal histories; machine throughput, respectively), and at intermediate levels (e.g., cost centers; areas/lines). 2. They are contextual in different ways by facility, by product line, by cost center, for example which enables stakeholders to evaluate a variety of potential causes for problematic events or trends. 3. The best metrics approaches for both of these disciplines recognize their interconnectedness (so balanced scorecards not only present KPIs from each perspective, but KPIs that explicitly link the two), total delivered cost, inventory turns, Return on Assets (ROA), etc. Sustainability measures have not offered the full potential value of critical information because thus far they have often been either too aggregate (think monthly water, electricity or gas bills) or too detailed (e.g., a steady stream of meter data), and they have generally been isolated from information about the factors and events that drive them. Since the financial impact of energy or water usage is easily measured through billings, (and consumption is really derived from the operations that consume resources), the focus of this paper will be on understanding how to make metrics more useful in terms of different levels of granularity, and establishing linkages to other data that exposes consumption drivers. 2

3 A Starting Point Based on a Commonly Used Operational KPI (and Its Components) Over the last 10 years, production industries of many types have adopted Overall Equipment Effectiveness (OEE) as the KPI that is used as a starting point for understanding the operational health of a machine, line, factory or business. The value of OEE is that it neatly links together several critical operational metrics: Equipment Availability (scheduled production time x %actual uptime) indicating whether the firm is appropriately balancing labor, plant, and production schedules, and managing to avoid unplanned downtime Product throughput the raw score indicating that available equipment was turning out product Quality to ensure that good throughput scores are only considered good if the product made is saleable For each of the component elements, actual performance is compared to targets, and those results factored against each other in a final calculation that illustrates how small losses in each area can, in fact, result in significant overall losses of opportunity to produce and sell. Establishing Consistent Granular Metrics Is a Key First Step For producers that are moving from billing-based views of utility cost and consumption, one of the first challenges is to extract more data from their facilities without creating a data-gathering burden. The right approach at this stage can set up a foundation that supports increasingly sophisticated reduction initiatives. Key criteria to consider in making the first investment are openness of the data management solution (can it connect to all critical assets and/or meters?) and the nature of the outputs. In addition, consider reporting and trending that are useful to management or engineering teams, and ensure that reports/ views are available that will help operators and supervisors drive appropriate behavior. For example, GE s Proficy* for Sustainability Metrics addresses these key criteria, as illustrated in the following screen captures. Figure 1 With a wide range of stakeholders needing access to varying levels of detailed consumption data, configurable objects like these represent an easy way to embed useful data and analytics into different role-based user cockpits or dashboards. 3

4 Resource Intensity The Metric That Links Operational and Sustainability Goals We can learn from this OEE model, and use it when considering how to add context to energy or water usage data: Availability data narrows focus to critical periods: Mapping utility usage information to the different categories of a facility s state (e.g., idle/after hours, producing, etc) is a critical first step in segmenting data; the events and behaviors that occur during production will be the data that drives insight into the most impactful reduction activities. - Breaking this down into different facility areas allows for KPIs and analysis to be run meaningfully when different areas in a facility may be on staggered schedules, or have dramatically different energy or water needs. Leveraging throughput data: Correlating consumption to production totals does more than provide a simple ratio of kwh/unit of production. It s the first step in understanding whether that ratio changes from shift to shift, plant to plant, or SKU to SKU, and is the starting point for asking why? Quality metrics emphasize all dimensions of waste: Ensuring that consumption is measured against raw throughput as well as final good product provides a granular metric that highlights all the aspects of waste inherent in scrap production the material loss, the wasted capital, the wasted labor and the wasted utilities. To illustrate these more clearly, we propose several metrics that build on the OEE concept, and can in fact be used alongside OEE to provide a balanced scorecard for Operations and Sustainability: (Note that here, we use the generic term consumption; in general, we d expect to measure water, gas, grid electricity, purchased steam, etc. individually). Production consumption/downtime consumption this measures energy or water inputs consumed during the scheduled available period in total, then compares it to the amount consumed during unplanned downtime providing a rough barometer of outright wasted usage and cost. To the degree that the nominal consumption can be modeled based on equipment consumption ratings, targets for each area in a facility can be established, which are useful for implementing alarm/escalation regimens based on trends within a day or shift. Consumption/unit of production this is a rough footprint added calculation that is useful for comparing performance at different times and places, and for different product families. Where nominal resource consumption rates are known for equipment or processes, it is possible to establish a target footprint for each unit of a given product family and to proactively trigger inquiry and remedial action when the total consumption related to a production order begins to trend and hold above the target. Consumption/unit of good production ( energy- or waterefficiency or intensity ) this refines the metric above by accounting for the wasted inputs that went into scrap. Its value is in the emphasis it adds to the understanding that the margin you earn from what you ship has to make up for what was not produced in saleable condition. As consumers, market makers in sales channels, and governments become more sophisticated in the ways they reward or incentivize good stewardship, this metric is likely to grow in usage and importance. Aligning Profitability and Stewardship Goals As with OEE and broader financial and operational metrics, these new KPIs meet the key criteria for being scalable to different levels of granularity, adaptable to different areas of focus, and interconnected to the controllable factors that drive them. It s that last point that establishes a clear path from metrics to analytics and the corrective behaviors that are at the heart of any mitigation strategy. A distinct advantage of using this approach is that it provides internal metrics that align with the profitability goals of the organization and with the stewardship goals. Looking at the resource-efficiency metric in particular, it s clear that improvements in operational effectiveness, which increase net quality or overall good output, will have the effect of lowering the energy- or water-intensity of a given lot of production. Likewise, outright reductions in consumption that result from equipment or process optimization, or investment in inherently resource-efficient capital will lower energy and water usage This is critical, because for firms that are capacity constrained, it is entirely possible that improvements in resource intensity may not necessarily translate to absolute reductions in use of energy or water; for example, a recovery in capacity may mean that overall shipments rise, while absolute use of water or energy remains stable or rises as well. 4

5 With so much external concern over absolute energy, carbon and water footprint, the proper use of that intensity metric will ensure that organizations know how to drive appropriate behaviors internally while communicating credibly to outside stakeholders. Consumption Data as an Operational Indicator The utility of this approach also goes beyond finding ways to allocate resource consumption between periods of good execution and quality and poor performance; it opens up avenues for consumption trends to be used as indicators of pending equipment, process, or quality issues: A power consumption measure on a liquid conveyance system that indicates above-normal electricity usage may be indicative of a quality variance in the product, with increased viscosity (and hence, higher current draw in the pumping system) being the tell-tale; Fluctuations in steam pressure and temperature may be the herald of an out-of-tune boiler control system that will compromise the mash process in a brewery, leading to re-work or waste; Simple differences in the water accounting between factories making the same products may expose inconsistencies in the way cleaning processes are executed calling for more rigorous procedural training and enforcement. Each of these scenarios offers a clear link between consumption data and an operational or quality-based recovery of value, with the integration of consumption data into the overall operations metrics and analytics being the key to enabling that value recovery. In our earlier paper, Information Strategies for Manufacturing Sustainability, we addressed in more detail the solution architectures that can be applied to embed measurement of sustainability data in common plant-side automation and IT systems. The conceptual architecture presented below illustrates the typical array of solutions capability in a plant; from control and operator interface systems managing the equipment and processes, through work-in-progress (WIP) tracking and quality management, to analytics and integration tools. Figure 2 Plant floor systems address a range of process control, tracking/coordination and analytical capabilities. Each of the areas noted can be considered a data source for the kind of analysis that allows consumption drivers to be characterized. An open data collection and reporting platform like GE Intelligent Platforms Proficy simplifies the work involved in correlating and analyzing data from functionally and technically disparate systems. 5

6 Resource Intensity The Metric That Links Operational and Sustainability Goals While each of these solutions is purchased to deliver specific functional capability to its primary stakeholders, each generates a body of data that is also useful in deciphering the links between operational and environmental performance. Systems such as WIP execution or quality measurement systems provide a core set of events to which a range of other data elements can be tied process parameters such as temperature, ph or viscosity; and sustainability data such as gas flow to a boiler, or current draw on a motor. That correlation of several data types makes it possible to construct the complete set of KPIs and to drive investigation when the KPI values are not on target! Conclusion As sustainability practices and measurements in manufacturing today tend to be less established compared to other disciplines, they are often perceived as a detached strategy from the tangible operations of production and profitability. However, manufacturers have a significant opportunity to align and balance both sustainability improvement objectives and operational continuous improvement approaches such as Lean by leveraging the parallels between them. Understanding how to make metrics more useful at various levels of granularity can help correlate sustainability measures with other operational data to expose consumption drivers enabling manufacturers to establish linkages and new KPIs that integrate critical information about the factors and events that drive consumption, interconnect them to controllable factors, and drive corrective actions. The obscurity of reduction goals can become transparent and palpable as commonly applied operational KPIs like OEE provide the context for measuring energy or water usage data to be used alongside operational measures enabling a balanced scorecard and helping manufacturers use resource-intensity metrics to balance operational and sustainability goals for a long-term competitive advantage. Solutions to Start or Accelerate Your Sustainability Initiatives Proficy for Sustainability Metrics Additional Information and Resources GE Intelligent Platforms Solutions for Sustainable Manufacturing White paper: Information Strategies for Manufacturing Sustainability GE Intelligent Platforms Contact Information Americas: or Global regional phone numbers are listed by location on our web site at GE Intelligent Platforms, Inc. All rights reserved. *Trademark GE Intelligent Platforms, Inc. All other brands or names are property of their respective holders GFT-797