Application of Generic CAD Models for Supporting Feature Based Assembly Process Planning

The paper discusses a novel geometric reasoning method that supports the definition of assembly sequence planning models departing from the CAD models of the parts involved. Specifically, by means of the presented algorithms that use a so-called collision point cloud approach one can determine the precise disassembly directions of parts having complex polygon mesh models. This information can be applied when defining assembly planning models both for suggesting precedence constraints as well as parameters for assembly operations. The presented heuristic algorithm was able to overcome certain shortcomings of earlier methods working with polygon mesh representations, and proved to be successful both in handling abstract and real-life industrial use cases. Working examples from both categories are presented in the paper

Optimal Robotic Assembly Sequence Planning: A Sequential Decision-Making Approach

The optimal robot assembly planning problem is challenging due to the necessity of finding the optimal solution amongst an exponentially vast number of possible plans, all while satisfying a selection of constraints. Traditionally, robotic assembly planning problems have been solved using heuristics, but these methods are specific to a given objective structure or set of problem parameters. In this paper, we propose a novel approach to robotic assembly planning that poses assembly sequencing as a sequential decision making problem, enabling us to harness methods that far outperform the state-of-the-art. We formulate the problem as a Markov Decision Process (MDP) and utilize Dynamic Programming (DP) to find optimal assembly policies for moderately sized strictures. We further expand our framework to exploit the deterministic nature of assembly planning and introduce a class of optimal Graph Exploration Assembly Planners (GEAPs). For larger structures, we show how Reinforcement Learning (RL) enables us to learn policies that generate high reward assembly sequences. We evaluate our approach on a variety of robotic assembly problems, such as the assembly of the Hubble Space Telescope, the International Space Station, and the James Webb Space Telescope. We further showcase how our DP, GEAP, and RL implementations are capable of finding optimal solutions under a variety of different objective functions and how our formulation allows us to translate precedence constraints to branch pruning and thus further improve performance. We have published our code at https://github.com/labicon/ORASP-Code.Comment: 6 conference page paper, 3 page appendix, 23 figure

Assemble Them All: Physics-Based Planning for Generalizable Assembly by Disassembly

Assembly planning is the core of automating product assembly, maintenance, and recycling for modern industrial manufacturing. Despite its importance and long history of research, planning for mechanical assemblies when given the final assembled state remains a challenging problem. This is due to the complexity of dealing with arbitrary 3D shapes and the highly constrained motion required for real-world assemblies. In this work, we propose a novel method to efficiently plan physically plausible assembly motion and sequences for real-world assemblies. Our method leverages the assembly-by-disassembly principle and physics-based simulation to efficiently explore a reduced search space. To evaluate the generality of our method, we define a large-scale dataset consisting of thousands of physically valid industrial assemblies with a variety of assembly motions required. Our experiments on this new benchmark demonstrate we achieve a state-of-the-art success rate and the highest computational efficiency compared to other baseline algorithms. Our method also generalizes to rotational assemblies (e.g., screws and puzzles) and solves 80-part assemblies within several minutes.Comment: Accepted by SIGGRAPH Asia 2022. Project website: http://assembly.csail.mit.edu

Disassembly 4.0: a review on using robotics in disassembly tasks as a way of automation

To successfully implement circular economy processes into present value chains, economic feasibility of disassembly processes is essential. Current developments in science and technology, such as artificial intelligence and Internet of Things, foster steep progression in the field of robotics. In this review, the current research on robotics in disassembly is investigated by a systematic literature review. The results were clustered in a framework system distinguishing between applied and basic research on the two main streams of disassembly automation research, namely, predefined processes and adaptable, flexible automation

Robust 2D Assembly Sequencing via Geometric Planning with Learned Scores

To compute robust 2D assembly plans, we present an approach that combines geometric planning with a deep neural network. We train the network using the Box2D physics simulator with added stochastic noise to yield robustness scores--the success probabilities of planned assembly motions. As running a simulation for every assembly motion is impractical, we train a convolutional neural network to map assembly operations, given as an image pair of the subassemblies before and after they are mated, to a robustness score. The neural network prediction is used within a planner to quickly prune out motions that are not robust. We demonstrate this approach on two-handed planar assemblies, where the motions are one-step translations. Results suggest that the neural network can learn robustness to plan robust sequences an order of magnitude faster than physics simulation.Comment: Presented at the 2019 IEEE 15th International Conference on Automation Science and Engineering (CASE

Engineering Support Systems for Industrial Machines and Plants

In the business of industrial machines and plants, rapid and detailed estimates for planning installation, replacement of equipment, or maintenance work are key requirements for meeting the demands for greater reliability, lower costs and for maintaining safe and secure operation. These demands have been addressed by developing technology driven by IT. When replacing equipment at complex building or plants with high equipment density, the existing state of the installation locations and transportation routes for old and new equipment need to be properly measured. We have met this need by developing parts recognition technology based on 3D measurement, and by developing high-speed calculation technology of optimal routes for installation parts. This chapter provides an overview of these development projects with some real business application results

Выбор рациональной последовательности сборки изделия как задача принятия решений

Automated synthesis of computer-aided assembly planning (CAAP) processes is a crucial task for engineering practice and design theory. It is of especial relevance for modern robotic industries, which need in technological assembly instructions to be described in-depth and in-detail as much as possible. The assembly sequence is a key design decision on which many operational properties of the product and economic characteristics of production depend.Choosing a rational assembly sequence planning (ASP) is a challenge. It requires significant computing resources and taking into consideration a large number of technical parameters and economic characteristics that affect the quality of design alternatives. Insights into the quality of alternatives are given as the expert’s preferences rather than as the numerical criteria.The abovementioned features do not allow us to apply the classical optimization methods or mathematical programming for making ASP decision. For this, most modern publications offer various search engine optimization methods based on biological and behavioral analogies. In this paradigm, it is believed that a set of acceptable alternatives that form the original choice space is a priori known. In most design situations this presumption is unrealistic.In engineering practice, considerable technological knowledge about the assembly of products for different function purposes is gained. These are mostly ad hoc data that exist in the form of rules, recommendations, recipes, heuristics, expert preferences, descriptions of successful precedents, etc. The paper suggests a new method for a choice of the rational assembly sequence based on the use of the decision theory apparatus. The proposal contains formalization of important design and technological heuristics, namely consistency with the dimensional chain system, geometric “freedom” during assembly, monotony in size, weight, accuracy, etc.A set of choice functions is open and can be completed by additional choice functions that describe engineering heuristics and decision rules that are relevant in the given design situation. The proposed approach allows the assessment and choice of alternatives according to several aspects or criteria. To do this, it is possible to use various methods of generating a common choice function from the totality of particular functions.Автоматизированный синтез процессов сборки сложных технических систем (Computer aided assembly planning, CAAP) – это важная проблема инженерной практики и теории проектирования. Она особенно актуальна для современных роботизированных производств, в которых технологические инструкции на сборку должны быть описаны с предельной глубиной и детализацией. Последовательность сборки представляет собой ключевое проектное решение, от которого зависят многие эксплуатационные свойства изделия и экономические характеристики производства.Выбор рациональной последовательности сборки (Assembly sequence planning, ASP) – это труднорешаемая задача. Она требует значительных вычислительных ресурсов и учета большого числа технических параметров и экономических характеристик, влияющих на качество проектных альтернатив. Представления о качестве альтернатив заданы не в виде числовых критериев, а в форме предпочтений эксперта.Перечисленные особенности не позволяют применить для решения ASP классические методы оптимизации или математического программирования. Для этого в большей части современных публикаций предлагаются различные методы поисковой оптимизации, основанные на биологических и поведенческих аналогиях. В данной парадигме считается, что априори известно множество допустимых альтернатив, образующее исходное пространство выбора. Это предположение является нереалистичным в большинстве проектных ситуаций.В инженерной практике накоплено множество технологических знаний о сборке изделий различного функционального назначения. В своем большинстве, это – неформализованные данные, существующие в виде правил, рекомендаций, рецептов, эвристик, предпочтений эксперта, описаний успешных прецедентов и др. В работе предлагается новый метод выбора рациональный последовательности сборки, основанный на использовании аппарата теории принятия решений. Предложена формализация важных конструкторских и технологических эвристик: согласованность с системой размерных цепей, геометрическая «свобода» при сборке, монотонность по габаритам, весу, точности и др.Множество функций выбора является открытым. Его можно пополнить дополнительными функциями выбора, описывающими инженерные эвристики и решающие правила, актуальные в данной проектной ситуации. Предложенный подход допускает оценку и выбор альтернатив по нескольким аспектам или критериям. Для этого можно использовать различные методы генерации общей функции выбора по совокупности частных функций

Анализ геометрической разрешимости при сборке сложных изделий как задача принятия решений

Computer aided assembly planning (CAAP) of complex products is an important and urgent problem of state-of-the-art information technologies. A configuration of the technical system imposes fundamental restrictions on the design solutions of the assembly process. The CAAP studies offer various methods for modelling geometric constraints. The most accurate results are obtained from the studies of geometric obstacles, which prohibit the part movement to the appropriate position in the product, by the collision analysis methods. An assembly of complex technical systems by this approach requires very high computational costs, since the analysis should be performed for each part and in several directions.The article describes a method for minimizing the number of direct checks for geometric obstacle avoidance. Introduces a concept of the geometric situation to formalize such fragments of a structure, which require checking for geometric obstacle avoidance. Formulates two statements about geometric heredity during the assembly. Poses the task of minimizing the number of direct checks as a non-antagonistic two-person game on two-colour painting of an ordered set. Presents the main decision criteria under uncertainty. To determine the best criterion, a computational experiment was carried out on painting the ordered sets with radically different structural properties. All the connected ordered sets are divided into 13 subclasses, each of which includes structurally similar instances. To implement the experiment, a special program has been developed that creates a random ordered set in the selected subclass, implements a game session on its coloration, and also collects and processes statistical data on a group of the homogeneous experiments.The computational experiment has shown that in all subclasses of the partial orders, the Hurwitz criterion with a confidence coefficient of 2/3 and that of Bayes-Laplace demonstrate the best results. The Wald and Savage criteria have demonstrated the worst results. In the experiment, a difference between the best and worst results reached 70%. With increasing height (maximum number of levels) of an ordered set, this difference tends to grow rapidly. In the subclass of pseudo-chains, all criteria showed approximately equal results.The game model of geometric obstacles avoidance allows formalizing data on geometric heredity and obtaining data on the composition and the minimum number of configurations, the test of which objectifies all existing-in-the-product geometric constraints on the movements of parts during assembly.Автоматизация проектирования процессов сборки сложных изделий – это важная и актуальная проблема современной информационной технологии. Фундаментальные ограничения на проектные решения сборочного передела накладывает геометрия технической системы. В исследованиях по CAAP предложены различные методы моделирования геометрических связей. Самые точные результаты дает исследования геометрических препятствии, которые запрещают движение детали в служебное положение в изделии, методами анализа столкновений. Для сборки сложных технических систем данный подход требует очень высоких вычислительных затрат, поскольку анализ следует выполнить для каждой детали и в нескольких направлениях.В статье описан метод минимизации числа прямых проверок на геометрическую разрешимость. Введено понятие геометрической ситуации, которое формализует такие фрагменты конструкции, для которых требуется проверка геометрическую разрешимость. Сформулированы два утверждения о геометрической наследственности при сборке. Задача минимизации числа прямых проверок поставлена как неантагонистиченская игра двух лиц по окрашиванию упорядоченного множества в два цвета. Приведены основные критерии принятия решений в условиях неопределенности. Для определения лучшего критерия проведен вычислительный эксперимент по окрашиванию упорядоченных множеств с радикально различными структурными свойствами. Все связные упорядоченные множества разбиты на 13 подклассов, в каждый из которых входят структурно подобные экземпляры. Для реализации эксперимента создана специальная программа, которая создает случайное упорядоченное множество в выбранном подклассе, реализует игровой сеанс по его окрашиванию, а также собирает и обрабатывает статистические данные по группе однородных экспериментов.Вычислительный эксперимент показал, что во всех подклассах частичных порядков лучшие результаты у критериев Гурвица с коэффициентом доверия 2/3 и Байеса-Лапласа. Худшие результаты продемонстрировали критерии Вальда и Севиджа. Разница между лучшими и худшими результатами достигала в эксперименте 70%. Эта разница имеет тенденцию к быстрому росту с увеличением высоты (максимального числа уровней) упорядоченного множества. В подклассе псевдоцепей все критерии показали примерно равные результаты.Игровая модель геометрической разрешимости позволяет формализовать данные о геометрической наследственности и получить данные о составе и минимальном числе конфигураций, проверка которых объективирует все геометрические ограничения на движения деталей при сборке, существующие в изделии

A methodology for aggregate assembly modelling and planning

The introduction of Concurrent Engineering highlights the need for a link between the early stages of product design and assembly planning. This thesis presents aggregate assembly process planning as a novel methodology to provide this link. The theory behind the research is to bring all aspects of product development together to consider assembly planning at the conceptual stage of design. Decisions taken during the early design stage not only have the greatest influence on production times and costs, but also should ensure that a design is easy to manufacture and assemble. An automated computer-based system has been developed to implement the methodology. The system generates aggregate assembly process plans which give details of feasible sequences, assembly process times and costs, resource requirements, and factory loadings. The Aggregate Assembly Modelling and Planning (AAMP) system employs object-oriented modelling techniques to represent designs, process planning knowledge, and assembly resources. The minimum information requirements have been identified, and a product model encompassing this data has been developed. An innovative factor of this thesis is to employ Assembly Feature Connections (AFCs) within the product model to represent assembly connectivity. Detailed generic assembly process models, functioning with limited design data, are used to calculate assembly criteria. The introduction of a detailed resource model to represent assembly facilities enables the system to calculate accurate assembly times, dependent on which resources are used within a factory, or even which factory is employed. A new algorithm uses the structure of the product model, process constraints and assembly rules to efficiently generate accurate assembly sequences. Another new algorithm loads the assembly operations onto workstations, ensuring that the capability and capacity are available. The aggregate assembly process planning functionality has been tested using products from industry, and has yielded accurate results that prove to be both technically feasible and realistic. Industrial response has been extremely favourable. Specific comments on the usefulness and simplicity of such a comprehensive system gives encouragement to the concept that aggregate assembly process planning provides the required link between the early stages of product design and assembly planning