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In a small (4.5 KW) diesel engine, Laser Induced Fluorescence (LIF) has been used to produce detailed oil film thickness measurements around the top piston ring and liner near midstroke. The flow is “Newtonian” under the ring in the sense that using a high shear rate viscosity at the liner temperature is appropriate. The geometry corresponds everywhere to that required for a valid Reynolds approximation. Classical boundary conditions are not applicable for the high strain rates (106-107 s-1) under the piston rings of typical modem engines. A new boundary condition is developed to explain the data. The exit surface shear stress is shown to scale with a Marangoni-like (surface tension gradient) effect. By increasing surface tension, it is possible to make substantial reductions in friction for a fixed high shear viscosity.

Experiments were done to quantify the dynamic motion of the piston and oil-film during piston impact on the cylinder bore, commonly known as “piston slap.” Parameters measured include engine block vibration, piston-skirt to liner separation, oil-film thickness between the piston and liner, and other engine operating conditions. Experimental parametric studies were performed covering the following: engine operating parameters - spark timing, liner temperature, oil-film thickness, oil type, and engine speed; and engine design parameters - piston-skirt surface waviness, piston-skirt/cylinder-liner clearance, and wrist-pin offset. Two dynamic modes of piston-motion-induced vibration were observed, and effects of changes in engine operating and design parameters were investigated for both types of slap. It was evident that engine design parameters have stronger effects on piston slap intensity, with piston-skirt/liner clearance and wrist-pin offset being the dominant parameters.

This paper contains both theorems and correlations based on the idea that there is a uniform metric for measuring the complexity of mechanical parts. The metric proposed is the logarithm of dimension divided by tolerance. The theorems prove that, on the average, for a given manufacturing process, the time to fabricate is simply proportional to this metric. We show corrleations for manual turning (machine lathe process), manual milling (machine milling process), and the lay-up of composite stringers. In each case the accuracy of the time estimate is as good as that of traditional cost estimation methods, but the effort is much less. The coefficient for composite lay-up compares well to that obtained from basic physiological data (Fitts Law).

Enhanced information management techniques made available through emerging Information Technology platforms hold a promise of providing significant improvements in both the effectiveness and efficiency of developing complex products. Determining actual management implementations that deliver on this promise has often proven elusive. Work in conjunction with the Lean Aircraft Initiative at MIT has revealed a straight forward use of Information Technology that portends significant cost reductions. By integrating previously separate types of data involved in the process of product development, engineers and designers can make decisions that will significantly reduce ultimate costs. Since the results presented are not specific to particular technologies or manufacturing processes, the conclusions are broadly applicable.

In a recent paper (Hoult & Meador, [1]) a novel method of estimating the costs of parts, and assemblies of parts, was presented. This paper proposed that the metric for increments of cost was the function log (dimension/tolerance). Although such log functions have a history,given in [1], starting with Boltzman and Shannon, it is curious that it arises in cost models. In particular, the thermodynamic basis of information theory, given by Shannon [2], seems quite implausible in the present context. In [1], we called the cost theory “Complexity Theory”, mainly to distinguish it from information theory. A major purpose of the present paper is to present a rigorous argument of how the log function arises in the present context. It happens that the agrument hinges on two key issues: properties of the machine making or assembling the part, and a certain limit process. Neither involves thermodynamic reasoning.