Evaluating The Fab Lifecycle And SubFab Service Maturity Model: Is There More To Gain?
Semiconductor manufacturers appreciate that maximizing fab profits requires high subfab functionality. Nevertheless, many plant managers view subfab maintenance as an unavoidable cost rather than an opportunity to lower overall expenses while increasing uptime. The experts at Edwards Vacuum delve into this dilemma, sharing insights for achieving balanced, optimized outcomes.
By Matt McDonald, Global Program Manager, and John Dalziel, Technical Program Manager, Edwards Vacuum
The vacuum and abatement systems that support semiconductor manufacturing processes in the fab are critical - if they are down, so too are the process tools they support. By the very nature of their function - to remove and render harmless process exhaust while maintaining the vacuum conditions required for the process to operate - they are exposed to harsh process chemicals and by-products that make regular service or replacement unavoidable.
Even more costly than planned maintenance is unexpected failure, which can impose additional costs for product losses and repairs to process equipment. Improving the management of vacuum and abatement systems offers significant productivity gains by minimizing both planned and unplanned downtime.Smart Manufacturing tools and Industrie 4.0 principles are becoming more accessible to manufacturers, where data-driven optimization of maintenance scheduling, namely predictive and proactive approaches, offer the benefit of minimizing downtime and risk of failures. For these approaches to achieve the desired results, differing levels of collaboration and domain expertise are required. The service maturity model helps to visualize progress towards this goal as movement up a maturity hierarchy. This progress must be considered in the context of the fab lifecycle, and, at a more granular level, individual product and process lifecycles. The service strategy must be agile enough to accommodate shifting priorities throughout lifecycles. A critical ingredient, and often the most significant contributor to successfully implementing a smarter approach, is the level of collaboration needed to enable the free flow of critical data. At the highest level, maintenance is transformed from a support cost to be minimized to a value-adding investment that increases productivity.
Figure 1. A service maturity model defines a hierarchy of services philosophies.Service Maturity Model
The mechanization of manufacturing, using machines to multiply the productivity of humans, was the basis of the first industrial revolution - Industrie 1.0 if you will. Ever since, as the role of machines has grown and evolved, and now as the industry embraces Industrie 4.0 and Smart Manufacturing, the methods and approaches to supporting and maintaining those machines have also evolved. The service maturity model (figure 1) classifies approaches to service in a hierarchy of five levels and visualizes the evolution as progression up the hierarchy. The lowest level is to do nothing - worry about it later. The next is reactive maintenance - run-to-fail and fix it when it breaks. At this level, maintenance costs are viewed as a non-productive expense and the focus is on minimizing that cost. The next level up is planned/preventive maintenance. Here manufacturers begin looking at the value added by maintenance through improvements in efficiency and performance.
Maintenance is scheduled periodically to occur before the equipment is likely to fail. Essential components of this approach are determining the optimal service interval, standardizing performance and procedures, and finding opportunities for improvement. Predictive maintenance, the next level, is condition-based and relies on increased monitoring of operational parameters to predict imminent failures. It seeks to maximize the time between interventions while avoiding unplanned failures. The highest level in the progression is prescriptive, in which close collaboration between the user and the provider and a shared commitment to continuous improvement promotes a prescriptive approach to maintenance with adjustments to machine operation that optimize outcomes to achieve the user's goals.
The progression described in the service maturity model allows service providers and consumers to understand their position in the hierarchy and align their programs to achieve desired outcomes. Service is not a one-size-fits-all proposition. Different customers and providers will find themselves at different levels. Indeed, the same customer may be at different levels in different parts of an overall manufacturing operation. For example, some Edwards on-chamber vacuum solutions run under a predictive model while many SubFab solutions are still managed with a run-to-fail approach. The service maturity model is most useful as a framework for determining the best next step in the continuous effort to improve user outcomes.
The greatest challenges posed by the maturity progression are related to the increasing collaboration required at each level. Every higher level requires greater understanding of the user's environment and process. At each level, the solutions must be more customized to reflect differences in processes. Each level requires more information to flow in both directions to characterize the state of the equipment, then assess and apply the required domain knowledge to enable continuous improvement.
The barriers are not always technical; for instance, they may be driven by organizational concerns about confidentiality and data security. Each level requires a broader view of the operational context and an increased understanding of other equipment and environmental variables that may affect performance and efficiency.