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005 20251121114907.0
010   $a9783032069115$b(electronic bk.)
010   $z9783032069108
024 7 $a10.1007/978-3-032-06911-5
035   $a(MiAaPQ)EBC32425704
035   $a(Au-PeEL)EBL32425704
035   $a(CKB)43658947400041
035   $a(DE-He213)978-3-032-06911-5
035   $a(EXLCZ)9943658947400041
100   $a20251121d2026      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aAdvances in Cycle Time Management /$fby Tin-Chih Toly Chen
205   $a1st ed. 2026.
210  1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2026.
215   $a1 online resource (208 pages)
225 1 $aEngineering Series
311 08$aPrint version: Chen, Tin-Chih Toly Advances in Cycle Time Management Cham : Springer,c2025 9783032069108 
327   $aCycle time management -- Cycle time prediction -- Cycle time modelling and analysis -- Management support -- Cycle time reduction.
330   $aThis book systematically introduces the principles and latest developments in cycle time management. With the rise of artificial intelligence, numerous advanced information technologies, such as Industry 4.0, big data, edge computing, and explainable artificial intelligence, have emerged. Factory engineers are exploring opportunities to apply these technologies to enhance the efficiency and effectiveness of cycle time management. To address this, the book conducts a preliminary investigation and outlines several practical actions that can be implemented. Factories worldwide are striving to reduce cycle times to increase their competitiveness and sustainability. Cycle time modeling and factor analysis are essential prerequisites, followed by accurate cycle time prediction and stringent control measures. Reducing cycle times can offer a competitive advantage in managing customer relationships. The successful strategies for shortening cycle times can also be applied to other product types or factories, a concept known as cycle time learning. All these efforts rely on comprehensive cycle time management activities. This book will be of use to professionals in industry as well as researchers and graduate students.
410  0$aEngineering Series
606   $aIndustrial engineering
606   $aProduction engineering
606   $aProduction management
606   $aBig data
606   $aArtificial intelligence
606   $aAutomobile industry and trade
606   $aIndustrial and Production Engineering
606   $aProduction
606   $aBig Data
606   $aArtificial Intelligence
606   $aAutomotive Industry
615  0$aIndustrial engineering.
615  0$aProduction engineering.
615  0$aProduction management.
615  0$aBig data.
615  0$aArtificial intelligence.
615  0$aAutomobile industry and trade.
615 14$aIndustrial and Production Engineering.
615 24$aProduction.
615 24$aBig Data.
615 24$aArtificial Intelligence.
615 24$aAutomotive Industry.
676   $a670
700   $aChen$b Tin-Chih Toly$0848082
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
912   $a9911047673003321
996   $aAdvances in Cycle Time Management$94477846
997   $aUNINA