A Quality-Based Business Model for Determining Non-product Investment: A Case Study From a Ford Automotive Engine Plant

by the U.S. industry, and it is estimated that approximately 80% of this is spent on correcting chronic failure of machines, system and people.” This clearly indicates the pressing need to reduce these non-product investments, and, in particular, maintenance costs in manufacturing facilities. Another important aspect of non-product investment, especially in the automotive industry, is that monies are typically made available to manufacturing plants to upgrade or overhaul critical equipment and tooling only if the plants are receiving new product models. For example, at Ford Motor Company, historically, if an engine plant is not slated to receive any new engine models for years to come, its non-product investment budget is dramatically reduced. In such plants, it becomes important to carefully utilize the limited budget resources available to selectively upgrade or overhaul equipment and tooling. The non-product investment model proposed in this article addresses this issue. Although the fi eld has been researched quite extensively, there are hardly any non-product investment and maintenance management models that can be applied universally (Scarf, 1997). The earliest form of maintenance models dates back to the 1950s and 1960s, when preventive maintenance (PM) concepts originated to reduce equipment failures and downtime (Dekker, 1996). Traditional PM plans were largely based on a combination of recommendations from manufacturers, legislatures and company-specifi c standards; very few plans were based on maintenance data (Rausand, 1998). In the 1970s the conditionbased maintenance (CBM) concept evolved and proved to be more effective than preventive maintenance programs based largely on time (Dekker, 1996). In CBM programs, the maintenance decisions are made by monitoring the actual state of equipment, such as lube-oil debris analysis and vibration monitoring. The other major shift in maintenance practice occurred during the late 1980s—the notion of reliability-centered maintenance (RCM). Introduced in the airline industry as early as the 1960s, some twenty years later it became popular in other industries as well (Fonseca and Knapp, 2000). The purpose of RCM was to minimize the PM cost by focusing on the most critical functions of the system, leaving out the other functions that are not critical in terms of their reliability (Rausand, 1998; Crocker and Kumar, 2000). One challenge of managing non-product investment, particularly maintenance, is precisely modeling the equipment deterioration data. Universal statistics such as average failure rate are more appropriate for complete replacement and thus may not be useful for most maintenance actions. More importantly, the data should capture the actual status of individual equipment