For revolving components like compressor stages in aero-engine, it is critical to ensure that the overall concentric performance of the assembly is extremely excellent to satisfy the requirements of vibration-free and noise-free. However, in practical production, it is hard to meet the target requirement by manual adjustments; in virtual assembly, it is difficult to build an effective deviation propagation model with traditional methods. This article focuses on two points: one is the assembly technique of multistage rotational optimization and the other is the deviation propagation model for revolving components assembly. The revolution joint was introduced in the unified Jacobian–Torsor model to provide the rotary regulating effects. This modified model has advantages of being able to consider rotating optimization, geometric tolerance, and percentage contribution compared with other mathematical methods. General formulas for the n-stage components assembly were derived including the deviation propagation function and optimization destination expression. Comparisons between three assembly techniques and experiments were made to prove the suggested method was feasible and of high practicability. It can be integrated with computer-aided design systems to propose assistance for operators in assembling stage or redesign parts tolerances where FEs’ percentage contributions can be obtained in design preliminary stage.

Purpose: Complicated workpiece, such as an engine block, has special rough locating datum features (i.e. six independent datum features) due to its complex structure. This locating datum error cannot be handled by current variation propagation model based on differential motion vectors. To extend variation prediction fields, this paper aims to solve the unaddressed variation sources to modify current model for multistage machining processes. Design/methodology/approach: To overcome the limitation of current variation propagation model based on differential motion vectors caused by the unaddressed variation sources, this paper will extend the current model by handling the unaddressed datum-induced variation and its corresponding fixture variation. Findings: The measurement results of the rear face with respect to the rough datum W and the pan face with respect to the hole Q by coordinate measuring machine (CMM) are −0.006 mm and 0.031 mm. The variation results for rear face and pan face predicted by the modified model are −0.009 mm and 0.025 mm, respectively. The discrepancy of model prediction and measurement is very small. Originality/value: This paper modifies the variation propagation model based on differential motion vectors by solving the unaddressed variation sources, which can extend the variation prediction fields for some complicated workpiece and is useful in the future work for many fields, such as process monitoring, fault diagnosis, quality-assured setup planning and process-oriented tolerancing.

Investment casting process produces high-precision castings, but there is a constant demand for improving the process capabilities, including dimensional accuracy and consistency. In this article, a state space modeling approach of investment casting process for dimensional variation is developed. This research focuses on the linear dimensional change (expansion or shrinkage) in the investment casting process. The generation, propagation and accumulation of the dimensional variation in the investment casting process are interpreted. In order to develop a mathematical model to describe the procedure above, a notion, the dimensional variation stream, is employed, and several key concepts, such as dimensional change rate, state vector and process parameter variation vector, are defined. The inherent relationships among these components are uncovered and finally bring about a State Space Model that describes the dimensional variation stream in the whole investment casting process. In the end, the usages of the developed model are illustrated and summarized via studying a case.

Assembly tolerance allocation in modern manufacturing industries is important because it directly affects product quality and manufacturing cost. Loose tolerances may cause quality deficiency while tight tolerances can increase the cost. It is significant to develop a reasonable tolerance allocation strategy for every assembly component combining the cost and quality demands. Traditionally, designers often adopt the single objective optimization with some kind of constraint or establish a comprehensive evaluation function combining several optimization objectives with different weights to solve the tolerance allocation problem. These approaches may not be desirable as it is difficult to adequately consider the interaction and conflict between the cost and quality demands. In this article, an assembly tolerance allocation method using coalitional game theory is proposed in an attempt to find a trade-off between the assembly cost and the assembly quality. First, the assembly tolerance allocation problem is formulated as a multi-objective optimization problem and the concept of the Pareto-optimal solution is introduced. Then, how the assembly tolerance allocation model is transformed into a coalitional game model is discussed, and a key technique of transforming the tolerance design variables into the game strategies is presented. Further, the Shapley value method of coalitional game based on each player's contribution evaluation to the profit of the whole coalition is given. Finally, the feasibility of the procedure is demonstrated through an example of vehicle front structure assembly.