Yicha Zhang

Feature based building orientation optimization for additive manufacturing

Purpose The purpose of this paper is to present research work based on the authors’ conceptual framework reported in the VRAP Conference 2013. It is related with an efficient method to obtain an optimal part build orientation for additive manufacturing (AM) by using AM features with associated AM production knowledge and multi-attribute decision-making (MADM). The paper also emphasizes the importance of AM feature and the implied AM knowledge in AM process planning. Design/methodology/approach To solve the orientation problem in AM, two sub-tasks, the generation of a set of alternative orientations and the identification of an optimal one within the generated list, should be accomplished. In this paper, AM feature is defined and associated with AM production knowledge to be used for generating a set of alternative orientations. Key attributes for the decision-making of the orientation problem are then identified and used to represent those generated orientations. Finally, an integrated MADM model is adopted to find out the optimal orientation among the generated alternative orientations. Findings The proposed method to find out an optimal part build orientation for those parts with simple or medium complex geometric shapes is reasonable and efficient. It also has the potential to deal with more complex parts with cellular or porous structures in a short time by using high-performance computers. Research limitations/implications The proposed method is a proof-of-concept. There is a need to investigate AM feature types and the association with related AM production knowledge further so as to suite the context of orientating parts with more complex geometric features. There are also research opportunities for developing more advanced algorithms to recognize AM features and generate alternative orientations and refine alternative orientations. Originality/value AM feature is defined and introduced to the orientation problem in AM for generating the alternative orientations. It is also used as one of the key attributes for decision-making so as to help express production requirements on specific geometric features of a desired part.

A new decision support method for the selection of RP process: knowledge value measuring

Many RP processes (rapid prototyping) have now been perfected and play an important role in creating prototypes as a support to the product development and in producing functional parts for direct applications. However, the selection of the right RP process or system for specific applications is becoming more difficult due to the expanding alternatives and their conflicting manufacturing properties, which form a classical multi-attribute decision-making (MADM) problem. To deal with the problem, this paper introduces a new method based on measuring manufacturing knowledge value extracted from RP processes. Knowledge unit and explicit knowledge value are redefined within the RP application context so as to apply an improved knowledge value measuring model which measures explicit knowledge value directly based on the deviation extent between knowledge units and the aspired application goals or preferences. The new method has some advantages when compared to former methods due to its simplicity and efficiency of using structured expert knowledge or production experience. It also has the potential to be widely applied in other fields where MADM problems exist, and to improve the efficiency of the present knowledge-based systems.

An integrated decision-making model for multi-attributes decision-making (MADM) problems in additive manufacturing process planning

Purpose – The purpose of this paper is to propose an integrated decision-making model for multi-attributes decision-making (MADM) problems in additive manufacturing (AM) process planning and for related MADM problems in other research areas. Design/methodology/approach – This research analyzed the drawbacks of former methods and then proposed two sub-decision-making models, “deviation model” and “similarity model”. The former sub-model aimed to measure the deviation extent of each alternative to the aspired goal based on analyzing Euclidean distance between them, whereas the latter sub-model applying grey incidence analysis was used to measure the similarity between alternatives and the expected goal by investigating the curve shape of each alternative. Afterwards, an integrated model based on the aggregation of the two sub-models was proposed and verified by a numerical example and simple case studies. Findings – The calculating results of the cited numerical example and the comparison to former related ...

Manufacturability analysis for additive manufacturing using a novel feature recognition technique

ABSTRACTAdditive Manufacturing (AM) increases much design freedom for designers to conceive complex parts. However, the increased complexity makes the manufacturability analysis difficult for the designed parts when applying traditional methods. To solve this problem, this paper introduces a new feature-based method for manufacturability analysis in AM by using Heat Kernel Signature. This method can both identify geometric features and manufacturing constrains which are defined in this paper for comprehensive analysis from the perspective of manufacturing to support the redesign and downstream process planning. A couple of example part models including a standard testing part for AM are used to demonstrate the feasibility of applying the proposed method for feature recognition and manufacturability analysis.

Physical assembly sequence optimisation for developing an integrated 3D reconstruction method

ABSTRACT In 3D reconstruction application domains, for example, repairing relics, bone fracture surgery, the reassembly of fragmented objects is required. Intensive research has focused on virtual 3D reconstruction but very little attention was paid to the physical assembly process where original segments are dealt with. To obtain a good reassembly result with reduced damage risk, assembly error and operation time, it is not enough to only use a 3D virtual model or a physical prototype model as assembly reference. The assembly sequence and the assembly operation should be investigated. To support the physical reconstruction, an integrated method which uses both virtual and physical prototyping technologies with human interaction is proposed. This paper mainly discusses the physical assembly sequence optimisation which is the partial implementation of the proposed method. An experimental pilot case study is presented to demonstrate the importance and potential of the method.

Generic Classification and Representation of Shape Features in Sheet-Metal Parts

This chapter presents classification and representation of shape features in sheet-metal parts. Shape features in a sheet-metal part model can be associated with volume subtraction from base-sheet (e.g., piercing/blanking operation), deformation/modification of base-sheet or forming operation on base-sheet. The shape features in a sheet-metal part model are classified as (i) Volumetric features and (ii) Deformation features. These features can also be classified as ‘2-dimensional (2D) features’ (volumetric features) and ‘3-dimensional (3D) features’ (deformation features) as a result of modification and forming of base-sheet. The thickness is constant for a sheet-metal part. Hence, the shape features in a sheet-metal part are also referred as constant thickness features. The representation, classification, and extraction procedures of the sheet-metal features are based on topology and geometry. The novelty is that the proposed classification and representation of sheet-metal features is based purely on shape entities and therefore it is possible to automatically extract the features from any sheet-metal part model. This enables the use of the proposed classification and representation to be unambiguous and application independent and to handle equivalences between feature labels and their representations among applications. The definition presented for a feature can also be extended to include application specific information.

Towards a new collaborative framework supporting the design process of industrial Product Service Systems

The main idea of this paper is to present a collaborative framework for PSS development process. Focused on the engineering phase, this research will use the modular ontology to support the management of the interfaces between various engineering knowledge involved in the PSS development process. The supporting platform is developed as a part of a collaborative framework that aims to manage the whole PSS lifecycle.