Integration of Perception, Global Planning and Local Planning in the Manufacturing Domain

Current approaches for factory automation have not yet fully succeeded in realizing an autonomous manufacturing system for mass customized, highly variant products. In this interdisciplinary work between computer science and mechanical engineering departments, the authors report on an integral approach for a cognitive manufacturing system which uses planning, perception and knowledge capabilities to reach a level of flexibility and robustness as found in a traditional human workshop. Integrating a bottom-up approach for local machining planning, a global planning system and a perception system, an autonomously operating manufacturing system can be realized. The integrated approach is validated using a simple yet characteristic example part that demonstrates the potential of the approach and the interplay and interfaces between the methods. Overall, the approach demonstrates that a specialized local planning system for machining can be effectively integrated with a general, global planning system and a perception system and thus be integrated in the manufacturing system

A Flexible Fixture and Reconfiguration Process for the Cognitive Machine Shop

To enable the autonomous fabrication of individual and customized parts, the flexibility provided by the planning system and the control system must be supported on the hardware level. To enable this degree of flexibility on the hardware level in the area of machining, an approach to the reconfiguration of fixtures for machine tools has been developed. By using a vice with jaws that can be exchanged with sufficient precision by a handling robot, the fixture can be changed to allow the fabrication of different parts. By having the machine tool machine the jaws directly, the fixture can be adapted to allow the fabrication of new, previously not produced parts. For the machining planning of the jaws the very same system as for machining planning of parts can be used. A prototype design of the flexible fixture device will be shown along with a process outline of the reconfiguration process on the system level. The approach and principle presented will enable a manufacturing system to fabricate a wide variety and even new parts without human interaction through the strong flexibility support on the hardware level and is therefore a stepping-stone towards the Cognitive Machine Shop

Generative design and CNC fabrication using shape grammars

Generative design and fabrication refers to the ability to autonomously generate designs while simultaneously generating all information to directly fabricate them. This technique is driven by the increasing need to rapidly and flexibly fabricate customized parts and individually designed products. For the automation of the design-to-fabrication process chain, intensive and dynamically updated knowledge from the domains of design and fabrication must be provided. To allow for a flexible, autonomous fabrication, the knowledge modeled must dynamically reflect the state of the fabrication system and its capabilities. This paper presents an approach to unify knowledge for generative design and generative fabrication using shape grammars. With shape grammars, the geometry of designs and their mapping to removal volumes corresponding to fabrication processes on CNC machine tools are represented. The process instructions for fabrication are included by augmenting the removal volume shapes with labels. A new shape grammar approach to represent designs and fabrication processes is presented and validated on an example functional part as a proof-of-concept. The approach enables pushing knowledge downstream, from design and process planning directly to the fabrication system itself providing a stepping stone towards awareness of machine capabilities in fabrication systems and autonomous process planning for customized parts

An application of shape grammars to planning for CNC machining

Planning for Computerized Numerical Control (CNC) fabrication requires generation of process plans for the fabrication of parts that can be executed on CNC enabled machine tools. To create such plans, a large amount of domain specific knowledge is required to map the desired geometry of a part to a manufacturing process, thus decomposing design information into a set of feasible machining operations. Approaches to automate this planning process still rely heavily on human capabilities, such as planning and reasoning about geometry in relation to machining capabilities. In this paper, the authors present a new, shape grammar-based approach for automatically creating fabrication plans for CNC machining from a given part geometry. To avoid the use of static feature sets and their pre-defined mappings to machining operations, the method encodes knowledge of fundamental machine capabilities. A method for generating a vocabulary of removal volume shapes based on the available tool set and machine tool motions is defined in combination with a basic rule set for shape removal covering tool motion, removal volume calculation and CNC code generation. The use of shape grammars as a formalism enables systematic formulation of hard and soft constraints on spatial relations between the volume to be removed and the removal volume shape for a machining operation. The method is validated using an example of machining a simple part on a milling machine. Overall, the approach and method presented is an enabler for the creation of an autonomous fabrication system and CNC machine tools that are able to reason about part geometry in relation to available capabilities and carry out on-line planning for CNC fabrication

Generative Konstruktions- und Fertigungs-Automation mittels Räumlicher Grammatiken und heuristischer Suchmethoden

To plan for CNC fabrication, a large amount of domain specific knowledge is required to map the desired geometry of a part to a manufacturing process. The newly developed method encodes knowledge of fundamental machine capabilities through the use of spatial grammars and applies it using heuristic search methods. A software implementation of the core method is presented and validated using several test cases. Overall, the approach and method presented is an enabler for the creation of autonomous fabrication systems and CNC machine tools that are able carry out on-line planning for CNC fabrication.Für die CNC gestützte Fertigung von Bauteilen ist eine große Menge spezifischen Wissens notwendig um der gewünschten Form eines Bauteils entsprechende Fertigungsprozesse zuzuordnen. Der neu entwickelte Ansatz verwendet Räumliche Grammatiken (sog. spatial grammars) um die grundlegenden Bearbeitungsmöglichkeiten darzustellen und Heuristische Suchmethoden um dieses Wissen anzuwenden. Eine Implementierung der Methode wird präsentiert und an Hand von mehreren Beispielen validiert. Insgesamt sind der Ansatz und die Methode ein Grundstein für die Schaffung von Autonomen Fertigungssystem und Werkzeugmaschinen die in der Lage sind selbstständig und spontan Ihre eigenen Aktivitäten zu planen

Next Generation Fabrication

Engineers design functional parts while machinists fabricate them. To overcome this gap between design and production the project Cognitive Machine Shop (CogMaSh) has been founded within the cluster of excellence Cognition for Technical Systems (CoTeSys). By integrating cognitive capabilities – which means planning, reasoning, self-awareness, learning – and integrating them into a fabrication system we will enable for the autonomous and unattended production of customized and high variant parts traditionally produced by workshops with their highly skilled people