Applied Economics in US Manufacturing
A number of terms have been used to discuss the use of digital technologies in manufacturing, including smart manufacturing, digital manufacturing, cloud manufacturing, cyber-physical systems, the industrial internet-of-things, and Industry 4.0. One of the applications of digital technologies is in the area of machinery maintenance. The three maintenance types that are, generally, referenced in this work include the following:
There are a wide range of estimates for the costs of machinery maintenance in manufacturing. Some estimates put it between 15 % and 70 % of the cost of goods produced. In terms of impacts of implementing advanced maintenance techniques, there are wide ranging estimates using a number of metrics (see the table below). The National Institute of Standards and Technology (NIST) is studying the costs and benefits of firms adopting advanced maintenance techniques. This work relates to NIST’s efforts to develop standards that facilitate advanced maintenance. As seen below, there are two publications that examine the economics of machinery maintenance in manufacturing.
Range of Impacts Identified in Various Publications for Implementing Advanced Maintenance Techniques, Percent Change
(see Figure 2.2 from NIST AMS 100-18 for source information on this figure)
The manufacturing atmosphere is continually changing with new technologies and standards being swiftly developed. Firms create competitive advantages using their knowledge, skills, supply chains, and processes to create superior products at lower prices. In such a competitive environment, efficient machinery maintenance methods can mean the difference between a thriving profitable firm and one that loses money and sales. Currently, at the national level there is limited understanding of the costs and losses associated with machinery maintenance or the different machinery maintenance techniques. This report examines the literature and data available for estimating the costs and losses relevant to different manufacturing maintenance techniques. It extends further to identify the data needed for making such estimates and the feasibility of collecting the relevant data. This report focuses on, but is not limited to, four categories of manufacturing: machinery, computer and electronic products, electrical equipment, and transportation equipment manufacturers.
The costs of maintenance and the potential effect on maintenance costs from adopting predictive maintenance techniques is not well documented at the national level. A number of data items need to be collected to estimate the costs and losses associated with maintenance. This paper examines the current literature on maintenance costs as it relates to advanced maintenance techniques and discusses the feasibility of collecting data to measure the relevant costs and losses. Discussions with manufacturing maintenance personnel suggests that manufacturers are willing and able to provide estimates or approximations of the data needed for estimating the manufacturing costs/losses relevant to advanced maintenance techniques. However, some discussants expressed uncertainty about the willingness to provide some of the data. Some items were not tracked; however, most believed that an approximation could be provided in these cases. In order to estimate maintenance cost for the manufacturing industry as a whole , a sufficient sample size is needed. Depending on the standard deviation, confidence interval, and accepted margin of error, a needed sample size of 77 is estimated, but could reasonably be as low as 14.