DETERMINATION OF VARIANCE OF TIME TO RECRUITMENT WITH INTER-DECISION TIME AS GEOMETRIC PROCESS WHEN THE THRESHOLD HAS THREE COMPONENTS

In this paper, the problem of time to recruitment is analyzed for a single grade manpower system using an univariate CUM policy of recruitment. Assuming policy decisions and exits occur at different epochs, wastage of manpower due to exits form a sequence of independent and identically distributed exponential random variables, the inter-decision times form a geometric process and inter-exist time form an independent and identically distributed random variable. The breakdown threshold for the cumulative wastage of manpower in the system has three components which are independent exponential random variables. Employing a different probabilistic analysis, analytical results in closed form for system characteristics are derived

Squashed-Slice Algorithm Based on STEP-NC for Multi-Material and Multi-Directional Additive Processes

Even though additive manufacturing is receiving increasing interest from aerospace, automotive, and shipbuilding, the legacy approach using tessellated form representation and cross-section slice algorithm still has the essential limitation of its inaccuracy of geometrical information and volumetric losses of final outputs. This paper introduces an innovative method to represent multi-material and multi-directional layers defined in boundary-representation standard model and to process complex sliced layers without missing volumes by using the proposed squashing operation. Applications of the proposed method to a bending part, an internal structure, and an industrial moulding product show the assurance of building original shape without missing volume during the comparison with the legacy method. The results show that using boundary representation and te squashing algorithm in the geometric process of additive manufacturing is expected to improve the inaccuracy that was the barrier of applying additive process to various metal industries.

Statistical Quality Control Charts Based on Hyper-Geometrically Distributed Data

In some production and administrative processes, the occurrence of certain events is best described by a hyper-geometric distribution, which in turn should be pictorially depicted by what should be called a “hyper-geometric chart (Hg-chart)” in the field of Statistical Quality Control (SQC). However, this has never been the practice, since the existence of such a chart is absent; as such, prompting administrators and process engineers to make use of already existing charts for approximately depicting hyper-geometric processes. In this article, an SQC chart for any hyper-geometric process has been developed for the total number of events in a fixed number of units. This chart has been referred to as the Hg-chart. The center line (CC), lower control limit (LCL) and the upper control limit (UCL) have been obtained for the proposed chart with a sketch of how the proposed chart should be if used for simulation. It has been recommended that simulation should be used to test the proposed chart as this could prove to be more efficient and appropriate for describing hyper-geometric data rather than using an inappropriate chart to be an approximation for solving the problem.