プロダクト（鉄道、発電プラント、圧縮機、電子顕微鏡、電子基板、家電）の信頼性・品質を担保するための機械系強度信頼性技術、材料科学、設計技術、製品の適正な保守サービス実現に向けた寿命推定や故障診断技術、およびプロダクトライフサイクルのための設計支援や設計自動化に向けたＡＩ／機械学習の応用に関する研究開発
機械強度信頼性、要素部品信頼性（歯車、軸受、回転体、振動）、ひずみ計測、故障診断、余寿命予測、設計技法、設計自動化、トポロジー最適化、業務プロセス/設計支援技術
Publishing Academic Papers:
Lifetime modelling for mechanical equipment by utilizing time-series data based-on the damage-based survival analysis (A trial for applying the model to the equipment in a chemical plant) , Transactions of the JSME, 2020
Abstract: A variety of health assessment technologies for mechanical systems utilizing time-series sensor data has been developed and are recently being applied to the maintenance work as a solution to the predictive maintenance. A majority of these technologies are the condition-based way which premises the existence of condition monitoring sensors such as accelerometers for the vibration monitoring of rotating mechanical elements. In the present study, authors suggested a load history-based methodology for identifying a descriptive and stochastic model of the useful life of mechanical systems to realize the predictive maintenance under constraints of sensing conditions. The methodology (Damage-based survival analysis, DbSA) was based on a parametric survival analysis by the maximum likelihood estimation assuming the Weibull distribution of the useful life. A random variable of the probability distribution was converted from the elapsed time to cumulative value of a function of time-series sensor data and parameters of this function were optimized to minimize the dispersion of the probability distribution by the particle swarm optimization. DbSA was applied to a historical record of a clogging problem in a strainer in a chemical plant and its time-series process data to demonstrate the usefulness. An identified damage-based lifetime model exhibited less than 50% smaller dispersion (coefficient of variance) compared to the timed-based probability distribution. In addition, an identified function composed of the process data implied an effect of the impurity generation to the clogging problem. If the identified model was applied to a dataset which was not used to the model identification, it was indicated that 3 of 8 cloggings were occurred when the damage-based failure probability was more than 50% although the time-based probability did not reach to this level at any time.
Prediction method of vibration response of electric motor considering casing as dynamic stiffness, Structural and Multidisciplinary Optimization, 2012
Abstract: The efficiency of designing a large-scale structure with many variables can often be increased by decomposing the design problem into less complex sub-problems. This article presents heuristic procedures of determining an appropriate design sequence to solve decomposed structural optimization problems using a sequential design (single-pass) strategy. One heuristic procedure exploits the monotonicity of a global constraint, which is included in all the sub-problems. Another procedure is based on the coupling strength of interactions between sub-problems, obtaining the appropriate design sequence and then verifying it with monotonicity analysis. The procedures are applied to two types of structural design problems; the metric for sequencing decomposed sub-problems can be obtained analytically for one design problem and numerically for another one. As a result, the sequencing procedures lead to satisfactory solutions at low computational cost, indicating their value for industrial product development. KeywordsStructural optimization–Decomposition method–Sequential design–Coupling strength–Monotonicity analysis.
超モノづくり部品大賞（環境・資源・エネルギー関連部品賞,2020）「腐食リスクを見える化できる「目視型環境診断センサー」
第66回大河内記念生産賞 電化非電化区間ともに走行可能な高速鉄道車両の開発(2020)
2022年度 日本機械学会賞（論文） 「多層ベローズ排気管の疲労寿命評価技術の開発」
2019年度 日本機械学会賞（論文） 「多層バルジ試験片を用いた薄膜の破壊強度評価手法の開発」
2019年度 日本機械学会賞（技術）「半導体ひずみセンサ「STREAL」の開発と事業化」
第76回電気学術振興賞 論文賞「超音波診断用CMUTの積層薄膜構造の検討」
事業のレジリエンス強化に貢献するIoT活用リスクマネジメントソリューション
https://www.hitachihyoron.com/jp/archive/2020s/2021/06/06a03/index.html?WT.mc_id=ksearch
実稼働情報を信頼性設計・保守に活用するIoT時代のアナリティクス
https://www.hitachihyoron.com/jp/archive/2010s/2016/07-08/12/index.html
社会インフラ設備における制御装置の安全性を支える腐食センシングソリューション
https://www.hitachihyoron.com/jp/archive/2010s/2018/06/11a02/index.html
