In this paper, the influence of the cutting plane as well as the orientation of the cavities in cross-coupled W-band waveguide filters are investigated. When waveguide filters are manufactured with the commonly known CNC (computer numerical control) milling technique, at least one cutting plane is required. The position of this cutting plane has an impact on the composition of the cavities, the manufacturing accuracy, and on the maximal number of transmission zeros (TZs) introduced by a direct source to load (SL) cross-coupling. Similar filter set-ups therefore may show different performances depending on the position of this cutting plane. To examine all these effects, three similar fourth-order W-band filter set-ups are realized with distinct cutting planes and different oriented cavities. The filters are compared in terms of the sensitivity to manufacturing tolerances, the maximal number of TZs introduced by a direct SL cross-coupling as well as their spurious mode performance.

Classic methodologies of DOE are widely applied in design, manufacture, qualitymanagement and related fields. The resulting data can be analysed with linear modelingmethods such as multiple regression which generates a set of equations, Y = F(X), thatenable us to understand how varying the mean of one or more inputs changes the mean of oneof more responses. To develop, scale-up and transfer robust processes to manufacturing wealso need to set the control tolerances of each critical X and understand the extentto which variation in the critical X’s propagate through to variation in theY’s and howthis may impact performance relative to requirements (or specifications). Visual toleranceanalysis provides a simple way to understand and reduce propagation of variation fromX’s toY’s usingmodels developed from DOE’s or historical data. This paper briefly introduces the conceptof tolerance analysis and extents this to visual tolerance analysis through defectprofiles and defect parametric profiles. With the help of visual tolerance analysis,engineering and statistical analysts can work together to find the key factors responsiblefor propagating undesired variation into responses and how to reduce these effects todeliver a robust and cost effective process. A case study approach is used to aidexplanation and understanding.

In mass production, the customer defines the constraints of assembled products byfunctional and quality requirements. The functional requirements are expressed by thedesigner through the chosen dimensions, which are linked by linear equations in the caseof a simple stack-up or non-linear equations in a more complex case. The customer qualityrequirements are defined by the maximum allowable number of out-of-tolerance assemblies.The aim of this paper is to prove that quality requirements can be accurately predicted inthe design stage thanks to a better knowledge of the statistical characteristics of theprocess. The authors propose an approach named Advanced Probability based ToleranceAnalysis (APTA), assessing the defect probability (called PD)that the assembled product has of not conforming to the functional requirements. Thisprobability depends on the requirements (nominal value, tolerance, capability levels) setby the designer for each part of the product and on the knowledge of production devicesthat will produce batches with variable statistical characteristics (mean value, standarddeviation). The interest of the proposed methodology is shown for linear and non-linearequations related to industrial products manufactured by the RADIALL SA Company.