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Distribution Modeling of Batch Forging Processes

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Modeling, Analysis and Control of Hydraulic Actuator for Forging

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Abstract

An effective model of batch forging processes is crucial in order to ensure the quality conformance control of batch productions. However, obtaining this model has proven difficult due to a variety of the raw forgings produced by manufacturing error, material variation, and geometric defects, etc. In this chapter, an online probabilistic extreme learning machine (ELM) is proposed to model batch forging processes. A probabilistic ELM is first developed to extract the distribution information of the batch forging processes from data. The stochastic property of the batch forging processes is then derived and processed. On this basis, a strategy is further developed to update the distribution model as new forging process data are collected. As a result, the model built is able to represent the distribution behavior of the batch forging processes well.

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Authors and Affiliations

  1. State Key Laboratory of High Performance Complex Manufacturing, School of Mechanical and Electrical Engineering, Central South University, Changsha, China

    Xinjiang Lu & Minghui Huang

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  1. Xinjiang Lu
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  2. Minghui Huang
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Correspondence to Xinjiang Lu .

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Lu, X., Huang, M. (2018). Distribution Modeling of Batch Forging Processes. In: Modeling, Analysis and Control of Hydraulic Actuator for Forging. Springer, Singapore. https://doi.org/10.1007/978-981-10-5583-6_3

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  • DOI: https://doi.org/10.1007/978-981-10-5583-6_3

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-5582-9

  • Online ISBN: 978-981-10-5583-6

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