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ABSTRACT:
Values of the Marshall 6 Swift (M6S) all-industry equipment cost indices are tabulated, dating back to their inception in 1913. The data since 1936 were correlated with time. It was found that both an exponential correlation and a bilinear correlation reproduced these data well, with correlation coefficients in excess of 0.98. The bilinear correlation consists of two straight lines, intersecting in the years 1966-1967. This bilinear correlation is favored for the prediction of future values of this index in the next century.
Key Words: Marshall & Swift equipment cost index, historical cost data, future cost predictions
One of the most popular and well-known tools for timescaling the capital investment costs for engineering projects is the Marshall & Swift (M&S) equipment cost index. Actually, 47 of these M&S industrial indices exist [1]. For example, there are separate indices developed and reported for five industries:
process;
electrical power;
mining and milling;
refrigeration; and
steam/power. Within the process industries, different M&S indices are published for the cement, chemical, glass, paper, and petroleum industries. An M&S all-industry equipment cost index also is compiled, and this composite index is the subject of this article.
The purpose of this article is not simply to present the temporal behavior of the M&S all-industry equipment cost index. Rather, the primary objective was to develop an accurate correlation for this behavior with two benefits in mind:
the ability to analytically compute historical values of M&S indices for possible use in engineering software, without having to resort to table lookup procedures when in a computer program or working on a spreadsheet; and
the prediction of future values of this index over a small future-time horizon, such as for 10 to 12 years.
Values in these various indices are updated regularly (often quarterly) and are reported in various engineering industry journals, such as Chemical Engineering, which is published by McGraw-Hill. The first exposure of most engineers to these indices, however, is usually in various classical and current textbooks [1, 3, 7] used in plant design and economics courses. Probably the most common application of these indices is to scale up a capital investment cost for a plant of given size or capacity as reported in an earlier year to an equivalent cost for...