LEADER 00580nam2 22002171i 450 001 990002299510403321 035 $a000229951 035 $aFED01000229951 035 $a(Aleph)000229951FED01 035 $a000229951 100 $a20030801d--------km-y0itay50------ba 200 1 $aGenetic engineering$ethe gene. Oxford,1990, v. 1, p. 361-408. 463 0$1001000220893 701 1$aDrlica,$bKarl$095988 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990002299510403321 959 $aFFABC 996 $aGenetic engineering$9388811 997 $aUNINA DB $aING01 LEADER 03953nam 22006855 450 001 9910993938003321 005 20250410125406.0 010 $a9783031853746 010 $a3031853741 024 7 $a10.1007/978-3-031-85374-6 035 $a(CKB)38337921600041 035 $a(DE-He213)978-3-031-85374-6 035 $a(MiAaPQ)EBC32005798 035 $a(Au-PeEL)EBL32005798 035 $a(EXLCZ)9938337921600041 100 $a20250410d2025 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aExplainable and Customizable Job Sequencing and Scheduling $eAdvancing Production Control and Management with XAI /$fby Tin-Chih Toly Chen 205 $a1st ed. 2025. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025. 215 $a1 online resource (IX, 126 p. 106 illus., 94 illus. in color.) 225 1 $aSpringerBriefs in Applied Sciences and Technology,$x2191-5318 311 08$a9783031853739 311 08$a3031853733 327 $aChapter 1. Explainable Artificial Intelligence (XAI) -- Chapter 2. Artificial Intelligence (AI) Applications in Job Sequencing and Scheduling -- Chapter 3. XAI Applications to Job sequencing and Scheduling -- Chapter 4. Explaining Artificial Neural Network and Deep Learning Applications in Job Sequencing and Scheduling -- Chapter 5. Explaining Genetic Algorithm and Other Bio-inspired Algorithm Applications in Job Sequencing and Scheduling -- Chapter 6. Tailoring Scheduling Rules Using XAI -- Chapter 7. XAI-enabled Edge Computing Application in Job Sequencing and Scheduling. 330 $aThis book systematically reviews the progress in explainable AI (XAI) and introduces the methods, tools, and applications of XAI technologies in job sequencing and scheduling. Relevant references and real case studies are provided as supporting evidence. To date, artificial intelligence (AI) technologies have been widely applied in job sequencing and scheduling. However, some advanced AI methods are not easy to understand or communicate, especially for factory workers with insufficient background knowledge of AI. This undoubtedly limits the practicability of these methods. To address this issue, explainable AI has been considered a viable strategy. XAI methods suitable for job sequencing and scheduling differ from those for other fields in manufacturing, such as pattern recognition, defect analysis, estimation, and prediction. This is the first book to systematically integrate current knowledge in XAI and demonstrate its application to manufacturing. 410 0$aSpringerBriefs in Applied Sciences and Technology,$x2191-5318 606 $aIndustrial engineering 606 $aProduction engineering 606 $aArtificial intelligence 606 $aData mining 606 $aUser interfaces (Computer systems) 606 $aHuman-computer interaction 606 $aIndustrial and Production Engineering 606 $aArtificial Intelligence 606 $aData Mining and Knowledge Discovery 606 $aUser Interfaces and Human Computer Interaction 615 0$aIndustrial engineering. 615 0$aProduction engineering. 615 0$aArtificial intelligence. 615 0$aData mining. 615 0$aUser interfaces (Computer systems) 615 0$aHuman-computer interaction. 615 14$aIndustrial and Production Engineering. 615 24$aArtificial Intelligence. 615 24$aData Mining and Knowledge Discovery. 615 24$aUser Interfaces and Human Computer Interaction. 676 $a670 700 $aChen$b Tin-Chih Toly$4aut$4http://id.loc.gov/vocabulary/relators/aut$0848082 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910993938003321 996 $aExplainable and Customizable Job Sequencing and Scheduling$94374750 997 $aUNINA