In setup planning, selection of proper datum is essential for attaining the specified tolerances of the machined component. At present, manufacturing industry is faced with the challenges of product variety and customization combined with the requirement of enhanced product quality at lower cost. Attaining the specified design tolerances is a key factor for the quality as well as the functionality of a component. It is the task of process planning to select appropriate processes and machines to ensure that design tolerance requirements are met. While machining a component, the different features of the component are assigned to different setups based on several criteria such as tool approach direction (TAD) of the feature, tolerance requirements, precedence relations, feature geometry, and feature interactions. Selection of proper datum for machining the features in a setup is a crucial task. Setup datum provides a definite and fixed position for machining the component. Selection of datum as well as its surface quality is very important for tolerance requirements of the features comprising the part. Geometrical tolerances such as parallelism, perpendicularity, angularity, and position need datum references. Some dimensional tolerances such as the distance between two parallel surfaces also need datum references. Therefore, the study of datum surface quality needs considerable attention.
Selection of the proper datum is one of the most challenging tasks that has received some research attention over the years. The approaches found in the literature for selection of datum are diversified in terms of criteria considered, such as total area of a face, its orientation, tolerance relation with other features, and symmetry and intricacy of the face. Large and maximum area face has been the most
widely used criterion for selecting the primary datum for machining [Gologlu, 2004;
Senthil Kumar et al., 1992]. However, surface area is not the only consideration for selecting datum. For proper location, the surface quality of datum is also important.
Usually, the datum surfaces are the machined surfaces [Gologlu, 2004; Roy and Sun, 1994; Senthil Kumar et al., 1992].
Many researchers consider tolerance relations among features as the prime criteria for selecting datum. Mei et al. [1995] proposed an artificial neural network based methodology for automatically selecting datums for rotational parts. The input to the neural network consists of the geometry of the part, and the tolerance specifications among the different part surfaces. The output of the network gives the datum surfaces selected for locating and clamping. The methodology proposed by Huang and Xu [2003] first considers critical tolerance relations among surfaces and then the area of a surface for datum selection for machining prismatic parts. To attain tight tolerance relationships, features should preferably be machined in the same setup using the same datum. Considering it, Guo et al. [2009] proposed a five- axis machining method for prismatic parts where features with different tool approach directions can be machined in the same setup with the same datum leading to better tolerance achievement. The authors performed optimization of operation sequences and setup determination using particle swarm optimization method.
A number of sources of manufacturing error are datum related such as locating error, clamping error, datum feature (surface) error, etc [Huang et al. 2004]. In a multi-station machining process, as the locating datums are changed for each station, machining errors get accumulated. Djurdjanovic and Ni [2003] modelled the influence of these errors on dimensional errors of a component for a multi-station machining process. Qin et al. [2007] proposed a model for prediction of workpiece machining error that considers workpiece position error, the workpiece elastic deformations and the inconsistent datum error.
It is well recognized that surface finish is one of the criteria for assessing the suitability of a face to be selected as locating datum [Hebbal and Mehta, 2008; Kim et al. 1996]. Ong and Nee [1998] proposed a fuzzy set based evaluation procedure to
Tolerances
assess the suitability of the features of a part to be used as fixturing features for machining of other features of the part. Surface finish of a feature is one of the criteria considered in addition to surface area, orientation, symmetry and intricacy.
Some researchers carried out theoretical and experimental studies on the effect of surface roughness of workpiece and datum on workpiece location and workpiece- fixture contact condition. Lee et al. [2001] studied the effect of surface roughness of the workpiece and datum on locating precision in multi-station machining process.
They found that the level of alignment precision decreases with increase in surface roughness. Deiab and Elbestawi [2005] presented the results of an experimental investigation on the tribological condition of workpiece-fixture contact surface considering surface roughness of the workpiece, fixture element, normal load, and workpiece material. It was observed that the friction coefficient decreases as the normal load increases.
However, the issue of effect of datum surface roughness on the geometrical tolerances of a component has not been well addressed. In the literature, not much work is available that relates the effect of datum surface roughness to the geometrical tolerances of a component. Although it is believed that a machined surface is to be used as a datum for machining, the appropriate range of surface roughness to achieve a particular tolerance level is not available in open literature.
However, the importance of selection of proper datum for tolerance requirements of the features in a setup can not be overlooked. In view of it, an experimental study is conducted to investigate the effect of datum surface roughness on two geometric tolerances, viz. parallelism and perpendicularity in machining of prismatic components. A simplified model is proposed for interpreting the experimental results. The knowledge obtained from the experimental results is incorporated in the knowledge-base of the setup planning expert system (described in Chapter 3) in the form of rules. The knowledge can be updated based on the shop floor feedback using the adaptive learning strategy discussed in Section 4.4, Chapter 4.
In this paragraph, a brief definition of parallelism and perpendicularity tolerances are presented. Parallelism specifies that all points on a given surface, axis, line or centre plane must be equidistant from a datum. Parallelism tolerance is the
maximum allowed deviation of parallelism from the true position. It requires a datum reference and may be defined between two planes, a plane and a line/axis or two lines/axes. A parallelism tolerance zone is formed by two hypothetical parallel planes/lines/axes and they are spaced apart by a distance equal to the parallelism tolerance. The toleranced feature should lie within this zone. Perpendicularity is the condition of a surface or an axis being at a right angle to a datum plane or axis. Perpendicularity tolerance is the maximum allowed deviation of the two features from right angle and it requires a datum reference.