State Matrix Representation of Assembly and Robot Planning

Robotica ◽  
1995 ◽  
Vol 13 (3) ◽  
pp. 259-272 ◽  
Author(s):  
S. M. Noorhosseini ◽  
A. S. Malowany
Keyword(s):  
Matrix Representation ◽  
Assembly Planning ◽  
Assembly Process ◽  
State Matrix ◽  
Goal Structures ◽  
Planning Time ◽  
New Approach ◽  
Planning Methods ◽  
Simple Matrix ◽  
Matrix Manipulation

SummaryA new approach to represent assembly called state matrix representation and an algorithm for automatic robot assembly planning based on this representation is proposed. The state matrix representation of assembly is configured by considering the inter-relationships of parts and objects involved in the initial and the goal structures. Thanks to this new representation, the planning lgorithm is straightforward and can be easily and efficiently implemented with simple matrix manipulation. Unlike other planning methods, the actions involved in the assembly process are not defined in advance but are generated at planning time. The syntax of actions are designed so that while directly reflecting the semantics of actions, they can be easily manipulated by the planner. Two examples of how to plan an assembly based on this representation are given in the paper.

The Datum Flow Chain: A Systematic Approach to Assembly Design and Modeling

1998 ◽  
Author(s):  
R. Mantripragada ◽  
D. E. Whitney
Keyword(s):  
Design Process ◽  
Systematic Approach ◽  
Assembly Planning ◽  
Assembly Process ◽  
Top Down ◽  
Assembly Design ◽  
Key Characteristics ◽  
Assembly Sequences

Abstract In order to be able to lay out, analyze, outsource, assemble, and debug complex assemblies, we need ways to capture their fundamental structure in a top-down design process, including the designer’s strategy for kinematically constraining and locating the parts accurately with respect to each other. We describe a concept called the “Datum Flow Chain” to capture this logic. The DFC relates the datum logic explicitly to the product’s key characteristics, assembly sequences, and choice of mating features, and provides the information needed for tolerance analyses. Two types of assemblies are addressed: Type-1 where the assembly process puts parts together at their prefabricated mating features, and Type-2 where the assembly process can incorporate in-process adjustments to redistribute variation. Two types of assembly joints are defined: mates that pass dimensional constraint from part to part, and contacts that merely provide support. The scope of DFC in assembly planning is presented using several examples. Analysis tools to evaluate different DFCs and select the ones of interest are also presented.

scholarly journals Dynamic Phasors Estimation Based on Taylor-Fourier Expansion and Gram Matrix Representation

2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Predrag Petrović ◽  
Nada Damljanović
Keyword(s):  
Matrix Representation ◽  
Series Representation ◽  
Gram Matrix ◽  
New Approach ◽  
Dynamic Phasors ◽  
New Strategy ◽  
Analytical Expressions ◽  
Numerical Complexity ◽  
Algebra Of Matrices

The paper presents a new approach to estimation of the dynamic power phasors parameters. The observed system is modelled in algebra of matrices related to its Taylor-Fourier-trigonometric series representation. The proposed algorithm for determination of the unknown phasors parameters is based on the analytical expressions for elements of the Gram’s matrix associated with this system. The numerical complexity and algorithm time are determined and it is shown that new strategy for calculation of Gram’s matrix increases the accuracy of estimation, as well as the speed of the algorithm with respect to the classical way of introducing the Gram’s matrix. Several simulation examples of power system signals with a time-varying amplitude and phase parameters are given by which the robustness and accuracy of the new algorithm are confirmed.

A Survey of Assembly Planning Based on Intelligent Optimization Algorithms

2008 ◽  
Author(s):  
Jihong Liu ◽  
Sen Zeng
Keyword(s):  
Ant Colony Algorithm ◽  
Optimization Algorithms ◽  
Combinatorial Problems ◽  
Assembly Sequence Planning ◽  
Assembly Planning ◽  
Future Research ◽  
Intelligent Optimization ◽  
Complete Problems ◽  
Intelligent Optimization Algorithms ◽  
Planning Methods

Assembly planning is one of the NP complete problems, which is even more difficult to solve for complex products. Intelligent optimization algorithms have obvious advantages to deal with such combinatorial problems. Various intelligent optimization algorithms have been applied to assembly sequence planning and optimization in the last decade. This paper surveys the state-of-the-art of the assembly planning methods based on the intelligent optimization algorithms. Five intelligent optimization algorithms, i.e. genetic algorithm (GA), artificial neural networks (ANN), simulated annealing (SA), ant colony algorithm (ACO) and artificial immune algorithm (AIA), and their applications in assembly planning and optimization are introduced respectively. The application features of the algorithms are summarized. At last, the future research directions of the assembly planning based on the intelligent optimization algorithms are discussed.

Decomposition of T2 Signal for Multivariate Assembly Process Control Using Bayesian Network

2011 ◽  
Vol 314-316 ◽  
pp. 2370-2374
Author(s):  
Yin Hua Liu ◽  
Yang Yang
Keyword(s):  
Bayesian Network ◽  
Control Charts ◽  
Mean Shift ◽  
Signal Decomposition ◽  
Assembly Process ◽  
New Approach ◽  
Root Cause ◽  
Monitoring And Diagnosis ◽  
The Mean ◽  
Interaction Change

The process monitoring and diagnosis in assembly process is important. Multivariate T2 control charts are applied to detect the mean shift and interaction change in the assembly process. However, T2 charts can not identify the root cause of the change. The traditional MTY method for T2 signal decomposition is computationally expensive, especially when the dimension of the variables is high. A new approach based on Bayesian network to identify the significant cause of T2 signals is proposed in this paper. The headlamp bracket case is used to illustrate the overall procedure. And the effectiveness of the proposed approach is evaluated.

A Human-Centered Virtual Assembly System

2009 ◽  
Vol 16-19 ◽  
pp. 796-800 ◽  
Author(s):  
Peng Chen ◽  
Ping Jun Xia ◽  
Yue Dong Lang ◽  
Ying Xue Yao
Keyword(s):  
Motion Capture ◽  
Virtual Assembly ◽  
Optimization Method ◽  
Virtual Manufacturing ◽  
Assembly System ◽  
Assembly Process ◽  
New Approach ◽  
Assembly Operation ◽  
Assembly Design ◽  
Human Modeling

Virtual manufacturing technology has become an effective method for decision and planning in manufacturing. Due to ergonomics problems are widely concerned in assembly design planning, a human-centered virtual assembly system framework is proposed for ergonomics analysis for assembly operation in this paper. The six-layer framework integrates virtual human modeling, motion capture and recognition, ergonomics evaluation and virtual assembly process planning as an organic whole. Data exchanging and system function are discussed based on this framework. The work in virtual reality (VR) technology, motion capture technology, ergonomics method and optimization method for implementing the system is also described. The framework would provide a new approach for the combination of virtual manufacturing and ergonomics analysis in the future.

A subassembly identification method for truss structures manufacturing based on community detection

2015 ◽  
Vol 35 (3) ◽  
pp. 249-258 ◽  
Author(s):  
Hao Cao ◽  
Rong Mo ◽  
Neng Wan ◽  
Fang Shang ◽  
Chunlei Li ◽  
...  
Keyword(s):  
Research Area ◽  
Truss Structures ◽  
Assembly Planning ◽  
Human Errors ◽  
Planning Time ◽  
Content Type ◽  
Automated Method ◽  
Assembly Sequences ◽  
Bounding Boxes ◽  
Oriented Bounding Boxes

Purpose – The purpose of this paper is to present an automated method for complicated truss structure subassembly identification. Design/methodology/approach – A community-detecting algorithm is introduced and adapted to reach the target. The ratio between oriented bounding boxes of parts is used as the weight to reflect the compact degree of assembly relationships. The authors also propose a method to merge nodes together at cut-vertex in model, by which the solving process could be accelerated. Findings – This method could identify the subassemblies of complex truss structures according to the specific requirements. Research limitations/implications – This research area is limited to truss structures. This research offers a new method in assembly sequences planning area. It could identify subassemblies in complex truss structures, with which the existing method is not adequate to deal. Practical implications – This method could facilitate the complex truss structures assembly planning, lower the human errors and reduce the planning time. Social implications – The method could inspire general assembly analysis planning. Originality/value – All authors of this paper confirm that this manuscript is original and has not been submitted or published elsewhere.

A New Study of Assembly Scheduling Effective Constraint Method in Assembly Planning

2013 ◽  
Vol 756-759 ◽  
pp. 4314-4317
Author(s):  
Yu Meng
Keyword(s):  
Assembly Planning ◽  
Assembly Process ◽  
Assembly Sequence ◽  
Interactive Process ◽  
Assembly Scheduling ◽  
Assembly Drawing ◽  
Level Information ◽  
Complex Equipment ◽  
Constraints Model ◽  
Constraint Method

This paper establishes an assembly planning model combined with the actual assembly process of the complex equipment and based on the equipment characteristic & interactive features. Adding constraints model for complex assembly steps which ensure the assembly validity by the hierarchical constraint assembly drawing built through a detailed analysis of complex constraint relations between the blocks and layers. The fact shows that the model can effectively express the establishment of the assembly sequence based on the equipment level information and hierarchical constraint relations, and in order to achieve the assembly relationship the decomposition and timing, make the interactive process is simple and easy to operate.

Using Yielded Cost As a Metric for Modeling Manufacturing Processes

2001 ◽  
Author(s):  
Daniel V. Becker ◽  
Peter Sandborn
Keyword(s):  
New Method ◽  
Manufacturing Processes ◽  
Assembly Process ◽  
Sequential Process ◽  
Process Step ◽  
New Approach ◽  
Complex Processes ◽  
Effective Cost ◽  
Step Step ◽  
Manufacturing Yield

Abstract Yielded cost is defined as cost divided by yield and can be used as a metric for representing an effective cost per good (non-defective) assembly for a manufacturing process. Although yielded cost is not a new concept, it has no consistent definition in engineering literature, and several different formulations and interpretations exist in the context of manufacturing and assembly. In manufacturing, yield is the probability that an assembly is non-defective. To find the effective cost per good assembly that is invested in the manufacturing or assembly process, cost is accumulated and divided by yield. This paper reviews and correlates existing yielded cost formulations and presents a new method that enables consistent measurement of sequential process flows. This new method views the yielded cost associated with an individual process step (step yielded cost) as the change in the process’s yielded cost when the step is removed from the process. This approach is preferred because it incorporates upstream and downstream information and because it provides a specific process step’s effective cost per good assembly that is independent of step order between steps that scrap defective product (i.e., test steps). Conventional wisdom dictates that the best way to improve a process is to increase the yield of the lowest yield step. The new approach developed in this paper produces an auxiliary cost that can be used to determine the best method of improving processes that, for complex processes, does not always correspond to improving the lowest yield step. Simple and complex assembly process examples are presented to demonstrate the interpretation of yielded cost. The new approach is applied to a microwave module (MWM) manufacturing and assembly process example.

scholarly journals An Automated Training of Deep Learning Networks by 3D Virtual Models for Object Recognition

Symmetry ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 496 ◽  
Author(s):  
Kamil Židek ◽  
Peter Lazorík ◽  
Ján Piteľ ◽  
Alexander Hošovský
Keyword(s):  
Deep Learning ◽  
Object Recognition ◽  
Augmented Reality ◽  
3D Models ◽  
Processing Unit ◽  
Assembly Process ◽  
Learning Networks ◽  
Embedded Devices ◽  
New Approach ◽  
Virtual Models

Small series production with a high level of variability is not suitable for full automation. So, a manual assembly process must be used, which can be improved by cooperative robots and assisted by augmented reality devices. The assisted assembly process needs reliable object recognition implementation. Currently used technologies with markers do not work reliably with objects without distinctive texture, for example, screws, nuts, and washers (single colored parts). The methodology presented in the paper introduces a new approach to object detection using deep learning networks trained remotely by 3D virtual models. Remote web application generates training input datasets from virtual 3D models. This new approach was evaluated by two different neural network models (Faster RCNN Inception v2 with SSD, MobileNet V2 with SSD). The main advantage of this approach is the very fast preparation of the 2D sample training dataset from virtual 3D models. The whole process can run in Cloud. The experiments were conducted with standard parts (nuts, screws, washers) and the recognition precision achieved was comparable with training by real samples. The learned models were tested by two different embedded devices with an Android operating system: Virtual Reality (VR) glasses, Cardboard (Samsung S7), and Augmented Reality (AR) smart glasses (Epson Moverio M350). The recognition processing delays of the learned models running in embedded devices based on an ARM processor and standard x86 processing unit were also tested for performance comparison.

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