Introduction to supply chain analytics: with examples in AnyLogic and anyLogistix software
The book offers a concise yet comprehensive introduction to supply chain analytics covering management, modeling, and technology perspectives. Designed to accompany the textbook "Global Supply Chain and Operations Management", it addresses the topics of supply chain analytics in more depth...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
Cham, Switzerland
Springer
[2024]
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| Schriftenreihe: | Classroom companion: business
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| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Zusammenfassung: | The book offers a concise yet comprehensive introduction to supply chain analytics covering management, modeling, and technology perspectives. Designed to accompany the textbook "Global Supply Chain and Operations Management", it addresses the topics of supply chain analytics in more depth. The book describes descriptive, predictive, and prescriptive supply chain analytics explaining methodologies, illustrating method applications with the use of training exercises, and providing numerous examples in AnyLogic and anyLogistix software. Throughout the book, numerous practical examples and short case studies are given to illustrate theoretical concepts. Along with AnyLogic and anyLogistix model development guidelines and examples, the book has two other distinct features. First, it reviews and explains novel frameworks and concepts related to data-driven decision-making and digital twins. Second, it shows how to use analytics to improve supply chain resilience. Without relying heavily on mathematical derivations, the book offers a structured presentation and explanation of major supply chain analytics techniques and principles in a simple, predictable format to make it easy to understand for students and professionals with both management and engineering backgrounds. Graduate/Ph.D. students and supply chain professionals alike would benefit from a structured and didactically-oriented concise presentation of the concepts, principles, and methods of supply chain analytics. Providing graduate students and supply chain managers with working knowledge of basic and advanced supply chain analytics, this book contributes to improving knowledge-awareness of decision-making in increasingly data-driven and digital environments. The book is supplemented by a companion website offering interactive exercises with the use of AnyLogic and anyLogistix software as well as Spreadsheet Modeling |
| Beschreibung: | XI, 167 Seiten Illustrationen, Diagramme |
| ISBN: | 9783031512407 |
Internformat
MARC
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| 245 | 1 | 0 | |a Introduction to supply chain analytics |b with examples in AnyLogic and anyLogistix software |c Dmitry Ivanov |
| 264 | 1 | |a Cham, Switzerland |b Springer |c [2024] | |
| 300 | |a XI, 167 Seiten |b Illustrationen, Diagramme | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a Classroom companion: business | |
| 505 | 8 | |a Analytics and model-based decision-making support -- Demand Forecasting, Production Planning and Inventory Control -- Discrete-Event Simulation of manufacturing processes and inventory control -- Facility location planning and network optimization -- Supply chain risk and resilience analytics | |
| 520 | |a The book offers a concise yet comprehensive introduction to supply chain analytics covering management, modeling, and technology perspectives. Designed to accompany the textbook "Global Supply Chain and Operations Management", it addresses the topics of supply chain analytics in more depth. The book describes descriptive, predictive, and prescriptive supply chain analytics explaining methodologies, illustrating method applications with the use of training exercises, and providing numerous examples in AnyLogic and anyLogistix software. Throughout the book, numerous practical examples and short case studies are given to illustrate theoretical concepts. Along with AnyLogic and anyLogistix model development guidelines and examples, the book has two other distinct features. First, it reviews and explains novel frameworks and concepts related to data-driven decision-making and digital twins. Second, it shows how to use analytics to improve supply chain resilience. Without relying heavily on mathematical derivations, the book offers a structured presentation and explanation of major supply chain analytics techniques and principles in a simple, predictable format to make it easy to understand for students and professionals with both management and engineering backgrounds. Graduate/Ph.D. students and supply chain professionals alike would benefit from a structured and didactically-oriented concise presentation of the concepts, principles, and methods of supply chain analytics. Providing graduate students and supply chain managers with working knowledge of basic and advanced supply chain analytics, this book contributes to improving knowledge-awareness of decision-making in increasingly data-driven and digital environments. The book is supplemented by a companion website offering interactive exercises with the use of AnyLogic and anyLogistix software as well as Spreadsheet Modeling | ||
| 650 | 4 | |a Supply chain management | |
| 776 | 0 | 8 | |i Erscheint auch als |n Online-Ausgabe |z 978-3-031-51241-4 |
| 856 | 4 | 2 | |m Digitalisierung UB Regensburg - ADAM Catalogue Enrichment |q application/pdf |u http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=035105196&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |3 Inhaltsverzeichnis |
| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-035105196 | |
Datensatz im Suchindex
| _version_ | 1812422644032602112 |
|---|---|
| adam_text |
VII Contents 1 Analytics and Model-Based Decision-Making Support. 1 1.1 Basics of Supply Chain Management. 2 1,1.1 Supply Chain Management. „. 2 1.1.2 Decisions in Supply Chain Management.». 3 1.2 Problems, Decisions, Systems, Data, and Models. 5 1.2.1 Problem and Decision. 5 1.2.2 Models and Data. 7 1.2.3 Data-Driven, Model-Based Decision-Making Support. 8 1.3 Methods of Supply Chain Analytics. 1.4 Mathematical Optimization. 10 1.5 Simulation. 11 1.5.1 Probability Theory and Mathematical Statistics. 11 1.5.2 Artificial Intelligence. 12 1.6 Dynamical System
Theory. 14 1.7 Applications of Supply Chain Analytics: Descriptive, Predictive, 9 and Prescriptive. 15 References. 18 2 Demand Forecasting, Production Planning, and Inventory Control. 21 2.1 Forecasting Methods and Accuracy. 22 2.1.1 Quantitative Forecasting Methods. 22 2.1.2 Forecasting Accuracy Quality. 23 2.1.3 Linear Regression. 24 2.1.4 Moving Average. 26 2.1.5 Simple Exponential Smoothing. 28 2.1.6 Double Exponential Smoothing. 30 2.2 Inventory
Control. 31 2.2.1 Order Quantity Planning for Cycle Inventory. 31 2.2.2 Reorder Point. 34 2.2.3 Service Levels and Safety Stock. 35 2.2.4 Single Period Systems ("Newsvendor Problem”). 37 2.2.5 Periodic Inventory Control. 38 2.2.6 Continuous Inventory Control. 40 2.3 Production Planning. 43 2.3.1 Problem Statement. 43 2.3.2 Linear Programming Method. 44 2.3.3 Application Example in Excel Solver. 45 References. 47
VIII Contents 3 Discrete Event Simulation of Manufacturing Processes and Inventory Control. 3.1 3.1.1 Manufacturing Process Planning. Queuing Theory. 50 50 3.1.2 3.1.3 Little's Law. Bottleneck Analysis/Theory of Constraints. 53 54 3.1.4 3.2 3.2.1 3.2.2 Trade-Off Capacity Utilization vs. Lead Time. Discrete Event Process Simulation in AnyLogic. Problem Statement. Development of Process Model in AnyLogic. 55 57 57 58 3.2.3 3.2.4 3.3 Development of Process Visualization in AnyLogic. Application Example. Case Study "EOQ and Inventory Control" in AnyLogic. 62 75 79 3.3.1 3.3.2 3.3.3 3.3.4 Developmentof an EOQ Model in AnyLogic. Developmentof Periodic Inventory Control Modelin AnyLogic. Development of a Continuous Inventory Control Model in AnyLogic. Events
and Application Example. References. 79 81 84 90 102 49 4 Facility Location Planning and Network Optimization. 103 4.1 Facility Location Planning. 104 4.1.1 4.1.2 4.2 4.3 4.4 4.4.1 4.4.2 4.4.3 Problem Statement. Center-of-Gravity Method. Network Optimization. anyLogistix Software. anyLogistix Case Study. Case Description. Greenfield Analysis. Network Optimization. References. 104 105 107 110 113 113 114 115 131 5 Supply Chain Risk and Resilience
Analytics. 133 5.1 Riskand Resilience in Supply Chains. 134 5.1.1 5.1.2 5.1.3 5.1.4 5.2 5.2.1 5.2.2 5.2.3 5.3 5.3.1 5.3.2 5.3.3 Supply Chain Risks and the Ripple Effect. Supply Chain Resilience. Supply Chain Resilience Analytics. Supply Chain Viability. anyLogistix Case Study. Performance Dashboard Design. Simulation Model Design. Disruption Simulation. anyLogistix Case Study: Comparison and Variation Experiments. Comparison Experiment. Variation Analysis. Managerial Recommendation. 134 136 138 140 141 141 142 I45 149 151 153 154
IX Contents 5,4 5.4.1 Digital Twin-Based Supply Chain Analytics. 155 Digital Supply Chain Twin. 155 5.4.2 anyLogistix as a Digital Supply Chain Twin. 157 References. 161 Supplementary Information Index. 165 |
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| author | Ivanov, Dmitry 1978- |
| author_GND | (DE-588)131871692 |
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| contents | Analytics and model-based decision-making support -- Demand Forecasting, Production Planning and Inventory Control -- Discrete-Event Simulation of manufacturing processes and inventory control -- Facility location planning and network optimization -- Supply chain risk and resilience analytics |
| ctrlnum | (OCoLC)1443590207 (DE-599)BVBBV049763845 |
| discipline | Wirtschaftswissenschaften |
| format | Book |
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| id | DE-604.BV049763845 |
| illustrated | Illustrated |
| indexdate | 2024-10-09T08:02:03Z |
| institution | BVB |
| isbn | 9783031512407 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-035105196 |
| oclc_num | 1443590207 |
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| owner | DE-1050 DE-355 DE-BY-UBR |
| owner_facet | DE-1050 DE-355 DE-BY-UBR |
| physical | XI, 167 Seiten Illustrationen, Diagramme |
| publishDate | 2024 |
| publishDateSearch | 2024 |
| publishDateSort | 2024 |
| publisher | Springer |
| record_format | marc |
| series2 | Classroom companion: business |
| spelling | Ivanov, Dmitry 1978- Verfasser (DE-588)131871692 aut Introduction to supply chain analytics with examples in AnyLogic and anyLogistix software Dmitry Ivanov Cham, Switzerland Springer [2024] XI, 167 Seiten Illustrationen, Diagramme txt rdacontent n rdamedia nc rdacarrier Classroom companion: business Analytics and model-based decision-making support -- Demand Forecasting, Production Planning and Inventory Control -- Discrete-Event Simulation of manufacturing processes and inventory control -- Facility location planning and network optimization -- Supply chain risk and resilience analytics The book offers a concise yet comprehensive introduction to supply chain analytics covering management, modeling, and technology perspectives. Designed to accompany the textbook "Global Supply Chain and Operations Management", it addresses the topics of supply chain analytics in more depth. The book describes descriptive, predictive, and prescriptive supply chain analytics explaining methodologies, illustrating method applications with the use of training exercises, and providing numerous examples in AnyLogic and anyLogistix software. Throughout the book, numerous practical examples and short case studies are given to illustrate theoretical concepts. Along with AnyLogic and anyLogistix model development guidelines and examples, the book has two other distinct features. First, it reviews and explains novel frameworks and concepts related to data-driven decision-making and digital twins. Second, it shows how to use analytics to improve supply chain resilience. Without relying heavily on mathematical derivations, the book offers a structured presentation and explanation of major supply chain analytics techniques and principles in a simple, predictable format to make it easy to understand for students and professionals with both management and engineering backgrounds. Graduate/Ph.D. students and supply chain professionals alike would benefit from a structured and didactically-oriented concise presentation of the concepts, principles, and methods of supply chain analytics. Providing graduate students and supply chain managers with working knowledge of basic and advanced supply chain analytics, this book contributes to improving knowledge-awareness of decision-making in increasingly data-driven and digital environments. The book is supplemented by a companion website offering interactive exercises with the use of AnyLogic and anyLogistix software as well as Spreadsheet Modeling Supply chain management Erscheint auch als Online-Ausgabe 978-3-031-51241-4 Digitalisierung UB Regensburg - ADAM Catalogue Enrichment application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=035105196&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Ivanov, Dmitry 1978- Introduction to supply chain analytics with examples in AnyLogic and anyLogistix software Analytics and model-based decision-making support -- Demand Forecasting, Production Planning and Inventory Control -- Discrete-Event Simulation of manufacturing processes and inventory control -- Facility location planning and network optimization -- Supply chain risk and resilience analytics Supply chain management |
| title | Introduction to supply chain analytics with examples in AnyLogic and anyLogistix software |
| title_auth | Introduction to supply chain analytics with examples in AnyLogic and anyLogistix software |
| title_exact_search | Introduction to supply chain analytics with examples in AnyLogic and anyLogistix software |
| title_full | Introduction to supply chain analytics with examples in AnyLogic and anyLogistix software Dmitry Ivanov |
| title_fullStr | Introduction to supply chain analytics with examples in AnyLogic and anyLogistix software Dmitry Ivanov |
| title_full_unstemmed | Introduction to supply chain analytics with examples in AnyLogic and anyLogistix software Dmitry Ivanov |
| title_short | Introduction to supply chain analytics |
| title_sort | introduction to supply chain analytics with examples in anylogic and anylogistix software |
| title_sub | with examples in AnyLogic and anyLogistix software |
| topic | Supply chain management |
| topic_facet | Supply chain management |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=035105196&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
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