An assembling algorithm for fixture in an assembly process planning system

Liu, Xiaojun; Xu, Xiaokang; Yi, Yang; Zhang, Ni; Zhang, Yang

doi:10.1177/0954405420904848

Cited by 5 publications

(4 citation statements)

References 25 publications

(24 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…4 Assembly Sequence Planning (ASP), piecing individual parts together in succession, is the vital stage of the production cycle because it comprises 40%-70% of the overall manufacturing cost and time. [5][6][7] ASP is an NP-hard problem that can generate ''n!'' feasible linear assembly sequences from a product with ''n'' number of parts.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Optimal assembly sequence planning with tool uncertainties

Champatiray

Bahubalendruni

Mahapatra

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part B:

View full text Add to dashboard Cite

Developing a practical and feasible assembly sequence plan for industrial applications is still challenging during product design and planning. Because of the need for more consideration of practical uncertainties, most of the assembly sequence plans generated by planners are inapplicable to real industrial-based problems. We have considered a crucial practical uncertainty attribute, tool uncertainties, in the current research. A novel approach has been proposed to generate optimal robotic assembly sequence plans by combining tool accessibility and part geometry. This research introduces two essential assembly tool accessibility attributes: tool-integrated geometric feasibility and tool-swept volume. In addition, the automatic extraction of tool accessibility attributes has been proposed. The proposed method is explained with a proper model and essential details such as liaison data, tool-integrated bounding box coordinates, tool-integrated geometric feasibility, and tool-swept volume data. Finally, the practical feasibility of the proposed method is verified for a different product configuration.

show abstract

Section: Introductionmentioning

confidence: 99%

“…4 Assembly Sequence Planning (ASP), piecing individual parts together in succession, is the vital stage of the production cycle because it comprises 40%–70% of the overall manufacturing cost and time. 5–7…”

Section: Introductionmentioning

confidence: 99%

Optimal assembly sequence planning with tool uncertainties

Champatiray

Bahubalendruni

Mahapatra

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part B:

View full text Add to dashboard Cite

show abstract

“…These methods are mainly classified into two categories: numerical programming method and heuristic method. All the numerical programming methods 13–16 start with an initial feasible layout and then optimize the scheme until the scheme cannot be further improved. The solutions obtained by these methods are very susceptible to the initial layout and usually cannot obtain the global optimal solution.…”

Section: Introductionmentioning

confidence: 99%

Fixture layout optimization for car dashboard based on N-X locating principle

Liu

Sun

2022

Proceedings of the Institution of Mechanical Engineers, Part B:

View full text Add to dashboard Cite

A fixture is a crucial component in the car dashboard manufacturing system and is used to position and restrain the car dashboard under external forces. However, the conventional fixture is only suitable for a specific type of car dashboard, which has poor adaptability. To this end, a new flexible fixture based on the N- X locating principle is proposed in this paper to adapt to different types of car dashboards. In the presented fixture, N clamping elements clamp the dashboard edge, while X movable supporting elements support the area close to the tool along the machining path. Furthermore, the fixture layout is optimized by combining a genetic algorithm (GA) and finite element analysis (FEA). In the optimization program, a multi-objective optimization function is established to suppress the deformation of the car dashboard. FEA is applied to calculate the machining deformation. The optimal locations of the fixture elements are determined by GA. A case is implemented to validate the proposed method and the results show that the maximum deformation and average deformation are reduced by 53.8% and 40%, respectively, compared with the empirical method.

show abstract

“…The intelligent optimization of the model uses the intelligent algorithm to solve the scheduling mathematical model. [8][9][10] Wen et al 11 embedded the trained neural network into the genetic algorithm to optimize remanufacturing production scheduling. Su et al 12 proposed a fuzzy genetic algorithm to solve the integrated optimization of steel production.…”

Section: Introductionmentioning

confidence: 99%

A new knowledgeable encapsulation method of steel production scheduling model

Chen

Jiang

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part B:

View full text Add to dashboard Cite

The steel production scheduling is a typical continuous/discrete hybrid process; it is dynamic and difficult to predict. The scheduling model is the core object of steel production scheduling, and its modeling methods directly affect the precise decision-making and execution efficiency of scheduling. However, the current linear program and simulation model do not yet realize the scheduling model quick reuse and dynamic construction. Therefore, a new model knowledgeable encapsulation method is proposed, which consists of a knowledgeable encapsulation framework and knowledgeable mapping method. The knowledgeable encapsulation framework includes the model knowledge description interface, model knowledge publication interface, model knowledge behavior interface, and a web platform. The interfaces and the platform are designed to help model providers to encapsulate the scheduling model in an open network environment. The mapping method is constructed to strengthen the relationship between the model knowledge. Finally, a knowledge encapsulation platform is established to verify the effectiveness of the model knowledge encapsulation method.

show abstract

An assembling algorithm for fixture in an assembly process planning system

Cited by 5 publications

References 25 publications

Optimal assembly sequence planning with tool uncertainties

Optimal assembly sequence planning with tool uncertainties

Fixture layout optimization for car dashboard based on N-X locating principle

A new knowledgeable encapsulation method of steel production scheduling model

Contact Info

Product

Resources

About