Abstract

There are two important aspects that will play important roles in future manufacturing systems: changeability and human-machine collaboration. The first aspect, changeability, concerns with the ability of production tools to reconfigure themselves to the new manufacturing settings, possibly with unknown prior information, while maintaining their reliability at lowest cost. The second aspect, human-machine collaboration, emphasizes the ability of production tools to put themselves on the position as humans’ co-workers. The interplay between these two aspects will not only determine the economical accomplishment of a manufacturing process, but it will also shape the future of the technology itself. To address this future challenge of manufacturing systems, the concept of Cognitive Factory was proposed. Along this line, machines and processes are equipped with cognitive capabilities in order to allow them to assess and increase their scope of operation autonomously. However, the technical implementation of such a concept is still widely open for research, since there are several stumbling blocks that limit practicality of the proposed methods. In this paper, we introduce our method to achieve the goal of the Cognitive Factory. Our method is inspired by the working mechanisms of a human’s brain; it works by harnessing the reasoning capabilities of cognitive architecture. By utilizing such an adaptive reasoning mechanism, we envision the future manufacturing systems with cognitive intelligence. We provide illustrative examples from our current research work to demonstrate that our proposed method is notable to address the primary issues of the Cognitive Factory: changeability and human-machine collaboration.

Highlights

  • The challenges of the 22nd century manufacturing system rely on the dynamic interaction between welldefined manufacturing processes and the adaptability of tools developed by engineers

  • This paper presents a fundamental concept of delivering theories from neuroscience into engineering tasks that are suitable to build modern manufacturing systems

  • The first aspect, changeability, concerns with the ability of production tools to reconfigure themselves to the new manufacturing settings, possibly with unknown information a priori, while maintaining their reliability at lowest cost

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Summary

Introduction

The challenges of the 22nd century manufacturing system rely on the dynamic interaction between welldefined manufacturing processes and the adaptability of tools developed by engineers. The concept of reconfigurable machine tools requires that the interfaces between the elements of the manufacturing system should be kept at minimum in order to enable reintegration This can be achieved through selfsustaining mechatronic configurable modules that contain all components needed for a satisfactory function. Our approach comes from the insight that the highest degree of changeability is still reached by human workshops with skilled workers and their cognitive capabilities, which enable them to react to changes, perceive their environment, plan their actions, and know what they are doing To achieve such a level for a production system, we need to look for a new strategy that puts production planning and automation in a cognitive manner. We conclude our work in section five and explain further direction of our research

Brain-inspired Processing with Cognitive Architecture
From CTS to Cognitive Factory
Cortically-inspired Network for Information Processing
Brain-connectome-inspired Network for Cognitive Architecture
Illustrative Examples
Cortically-inspired Sensor Fusion Network
Model-based Mobile Manipulator
Experimental Results and Discussion
Conclusion
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