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• catalog abstract ""Human Learning From Learning Curves to Learning Organizations covers a broad range of learning models and related topics beginning with learning curves to recent research on learning organizations. The book's focus is to enable researchers and practitioners to forecast any organization's "learning needs" using the prediction aspects of an array of learning models."--Jacket.".
• catalog contributor b12388505.
• catalog created "2000.".
• catalog date "2000".
• catalog date "2000.".
• catalog dateCopyrighted "2000.".
• catalog description ""Human Learning From Learning Curves to Learning Organizations covers a broad range of learning models and related topics beginning with learning curves to recent research on learning organizations. The book's focus is to enable researchers and practitioners to forecast any organization's "learning needs" using the prediction aspects of an array of learning models."--Jacket.".
• catalog description "2 Factors that Influence the Learning Curve 9 -- 2.1 Methods Improvement -- 2.2 Worker selection -- 2.3 Previous experience -- 2.4 Training -- 2.5 Motivation -- 2.6 Job complexity -- 2.7 Number of repetitions (or, cycles) -- 2.7.1 Does learning continue forever? -- 2.7.2 How many cycles to reach Time Standard -- 2.7.3 Size of job orders -- 2.8 Length of the task -- 2.9 Errors generated -- 2.10 Forgetting -- 2.11 Continuous improvement -- 3 Summary of Learning Models-No Forgetting 25 -- 3.1 Power model -- 3.1.1 Finding the total time to complete m cycles, 'T[subscript m]' -- 3.1.2 To find the average time to complete m cycles -- 3.2 Cumulative Average power model -- 3.3 Stanford B model -- 3.4 DeJong's learning model -- 3.5 Dar-El's modification of DeJong's model -- 3.6 Dar-El/Ayas/Gilad Dual-Phase model Operations -- 3.6.1 Determining the learning parameters -- 3.6.2".
• catalog description "Calculating the production time for 'm' cycles -- 3.6.3 An example -- 3.7 Bevis/Towill learning model -- 3.8 Other learning models -- 3.8.1 Hancock Linear model -- 3.8.2 Pegels model -- 3.8.3 Dar-El/Altman model -- 3.8.4 Yet other learning models -- 3.9 Learning models in review -- 4 Determining the Power Curve Learning Parameters 57 -- 4.1 Determining parameters from actual data -- 4.2 Predicting parameter values without prior experience -- 4.2.1 Predicting the learning constant 'b' -- 4.2.2 Predicting the performance time for the first cycle -- 4.2.3 Reviewing the methodology for predicting 'b' and 't[subscript 1]' values -- 4.3 Resuscitating DeJong's learning curve model -- 4.4 Predicting the number of repetitions to reach standard -- 4.5 Assessing previous experience -- 5 A Summary of Learning Models with Forgetting 77 -- 5.1 Background to the "L-F-R" process -- 5.2".
• catalog description "Developing optimal training schedules -- 7.2.2 Cost function -- 7.2.3 Defining the optimization problem -- 7.2.4 Analytical solution of a simplified model -- 7.2.5 Empirical determination of 'g' and 'h' -- 8 Learning in the Plant: The- Beginnings of Organizational Learning 159 -- 8.1 Learning at the firm level: the progress function -- 8.2 Learning with new processes and products -- 8.2.1 Ferdinand K. Levy: Adaptation in the production process -- 8.2.2 Denis Towill (and co-authors): Industrial dynamics family of learning curve models -- 8.3 Learning at the firm level and econometric models -- 8.4 Learning in aggregate and capacity planning -- 8.5 Learning in artificial intelligence -- 8.6 Impact on Quality and JIT -- 8.6.1 Continuous improvements in the manufacture of semiconductors -- 8.6.2 Affect of quality factors on learning -- 9 Learning Organizations 185 -- 9.1".
• catalog description "Does 'Learning Organization' differ from 'Organizational Learning'? -- 9.2 A primer on Learning Organizations -- 9.2.1 Learning Organization applications -- 9.3 Linking individual and plant learning to Learning Organizations -- 9.4 Teams and team operation -- 9.4.1 Work teams--past and present -- 9.4.2 Single loop vs. double loop learning in teams -- 9.5 Developing into a Learning Organization -- 9.5.1 Developing teams for the Learning Organization -- 9.5.2 Structure of the teams -- 10 A Summary and Future Research on Human Learning 211 -- 10.1 Individual learning -- 10.1.1 Experience -- 10.1.2 Learning-Forgetting-Relearning (L-F-R) phenomenon -- 10.1.3 Estimating learning parameters -- 10.1.4 Learning with long cycle times/large products -- 10.1.5 Optimal training schedules -- 10.2 Team/crew/group learning -- 10.3 Plant learning -- 10.4 Learning Organization.".
• catalog description "How should L-F-R characteristics be measured? -- 5.3 Factors that influence the "L-F-R" phenomenon -- 5.3.1 Break (or interruption) length -- 5.3.2 Previous experience -- 5.3.3 Job complexity -- 5.3.4 Work engaged in during the break period -- 5.3.5 Cycle time of the task -- 5.3.6 Relearning curve -- 5.3.7 When relearning is a single observation point -- 5.4 Modeling the "L-F-R" phenomenon -- 5.4.1 Modeling "L-F-R" for multiple repetitions -- 5.4.2 Proposal for a "L-F-R" model -- 6 Applications (with and Without Forgetting) 99 -- 6.1 LC in time & motion study -- 6.2 LC in assembly line design -- 6.2.1 Optimal number of stations under learning -- 6.2.2 Minimizing the makespan for assembly (production) lines under learning -- 6.2.3 LC with mixed-model assembly lines -- 6.2.4 LC in assembly lines for new products -- 6.2.5 Optimizing "cycle time: number of stations" under learning constraints -- 6.3".
• catalog description "Includes bibliographical references (p. [219]-232) and index.".
• catalog description "LC with long cycle time tasks -- 6.3.1 A model for learning behavior in long cycle time tasks -- 6.3.2 Estimating the learning constant 'b' under conditions of forgetting -- 6.3.3 Predicting performance times for long cycle times -- 6.4 LC in batch size, or lot size production -- 6.5 LC in a Group Technology (GT) environment -- 6.6 Learning in a JIT environment -- 6.7 'Speed-Accuracy' in a learning environment -- 6.7.1 Speed-Accuracy via Buck & Cheng (1993) -- 6.7.2 Speed-Accuracy via Vollichman (1993) -- 6.8 Learning curves in machining operations -- 7 Cost Models for Optimal Training Schedules 135 -- 7.1 Near optimal training schedules via experimentation: a military application -- 7.1.1 Problem description -- 7.1.2 Pilot study -- 7.1.3 Study objectives -- 7.1.4 Experimental plan -- 7.1.5 Partial experimental results -- 7.1.6 Improving the efficiency of the training schedule -- 7.2".
• catalog extent "xi, 236 p. :".
• catalog identifier "0792379438".
• catalog isPartOf "International series in operations research & management science ; 29".
• catalog issued "2000".
• catalog issued "2000.".
• catalog language "eng".
• catalog publisher "Boston : Kluwer Academic Publishers,".
• catalog subject "153.1/58 21".
• catalog subject "Adult learning.".
• catalog subject "LC5225.L42 D36 2000".
• catalog subject "Organizational learning.".
• catalog tableOfContents "2 Factors that Influence the Learning Curve 9 -- 2.1 Methods Improvement -- 2.2 Worker selection -- 2.3 Previous experience -- 2.4 Training -- 2.5 Motivation -- 2.6 Job complexity -- 2.7 Number of repetitions (or, cycles) -- 2.7.1 Does learning continue forever? -- 2.7.2 How many cycles to reach Time Standard -- 2.7.3 Size of job orders -- 2.8 Length of the task -- 2.9 Errors generated -- 2.10 Forgetting -- 2.11 Continuous improvement -- 3 Summary of Learning Models-No Forgetting 25 -- 3.1 Power model -- 3.1.1 Finding the total time to complete m cycles, 'T[subscript m]' -- 3.1.2 To find the average time to complete m cycles -- 3.2 Cumulative Average power model -- 3.3 Stanford B model -- 3.4 DeJong's learning model -- 3.5 Dar-El's modification of DeJong's model -- 3.6 Dar-El/Ayas/Gilad Dual-Phase model Operations -- 3.6.1 Determining the learning parameters -- 3.6.2".
• catalog tableOfContents "Calculating the production time for 'm' cycles -- 3.6.3 An example -- 3.7 Bevis/Towill learning model -- 3.8 Other learning models -- 3.8.1 Hancock Linear model -- 3.8.2 Pegels model -- 3.8.3 Dar-El/Altman model -- 3.8.4 Yet other learning models -- 3.9 Learning models in review -- 4 Determining the Power Curve Learning Parameters 57 -- 4.1 Determining parameters from actual data -- 4.2 Predicting parameter values without prior experience -- 4.2.1 Predicting the learning constant 'b' -- 4.2.2 Predicting the performance time for the first cycle -- 4.2.3 Reviewing the methodology for predicting 'b' and 't[subscript 1]' values -- 4.3 Resuscitating DeJong's learning curve model -- 4.4 Predicting the number of repetitions to reach standard -- 4.5 Assessing previous experience -- 5 A Summary of Learning Models with Forgetting 77 -- 5.1 Background to the "L-F-R" process -- 5.2".
• catalog tableOfContents "Developing optimal training schedules -- 7.2.2 Cost function -- 7.2.3 Defining the optimization problem -- 7.2.4 Analytical solution of a simplified model -- 7.2.5 Empirical determination of 'g' and 'h' -- 8 Learning in the Plant: The- Beginnings of Organizational Learning 159 -- 8.1 Learning at the firm level: the progress function -- 8.2 Learning with new processes and products -- 8.2.1 Ferdinand K. Levy: Adaptation in the production process -- 8.2.2 Denis Towill (and co-authors): Industrial dynamics family of learning curve models -- 8.3 Learning at the firm level and econometric models -- 8.4 Learning in aggregate and capacity planning -- 8.5 Learning in artificial intelligence -- 8.6 Impact on Quality and JIT -- 8.6.1 Continuous improvements in the manufacture of semiconductors -- 8.6.2 Affect of quality factors on learning -- 9 Learning Organizations 185 -- 9.1".
• catalog tableOfContents "Does 'Learning Organization' differ from 'Organizational Learning'? -- 9.2 A primer on Learning Organizations -- 9.2.1 Learning Organization applications -- 9.3 Linking individual and plant learning to Learning Organizations -- 9.4 Teams and team operation -- 9.4.1 Work teams--past and present -- 9.4.2 Single loop vs. double loop learning in teams -- 9.5 Developing into a Learning Organization -- 9.5.1 Developing teams for the Learning Organization -- 9.5.2 Structure of the teams -- 10 A Summary and Future Research on Human Learning 211 -- 10.1 Individual learning -- 10.1.1 Experience -- 10.1.2 Learning-Forgetting-Relearning (L-F-R) phenomenon -- 10.1.3 Estimating learning parameters -- 10.1.4 Learning with long cycle times/large products -- 10.1.5 Optimal training schedules -- 10.2 Team/crew/group learning -- 10.3 Plant learning -- 10.4 Learning Organization.".
• catalog tableOfContents "How should L-F-R characteristics be measured? -- 5.3 Factors that influence the "L-F-R" phenomenon -- 5.3.1 Break (or interruption) length -- 5.3.2 Previous experience -- 5.3.3 Job complexity -- 5.3.4 Work engaged in during the break period -- 5.3.5 Cycle time of the task -- 5.3.6 Relearning curve -- 5.3.7 When relearning is a single observation point -- 5.4 Modeling the "L-F-R" phenomenon -- 5.4.1 Modeling "L-F-R" for multiple repetitions -- 5.4.2 Proposal for a "L-F-R" model -- 6 Applications (with and Without Forgetting) 99 -- 6.1 LC in time & motion study -- 6.2 LC in assembly line design -- 6.2.1 Optimal number of stations under learning -- 6.2.2 Minimizing the makespan for assembly (production) lines under learning -- 6.2.3 LC with mixed-model assembly lines -- 6.2.4 LC in assembly lines for new products -- 6.2.5 Optimizing "cycle time: number of stations" under learning constraints -- 6.3".
• catalog tableOfContents "LC with long cycle time tasks -- 6.3.1 A model for learning behavior in long cycle time tasks -- 6.3.2 Estimating the learning constant 'b' under conditions of forgetting -- 6.3.3 Predicting performance times for long cycle times -- 6.4 LC in batch size, or lot size production -- 6.5 LC in a Group Technology (GT) environment -- 6.6 Learning in a JIT environment -- 6.7 'Speed-Accuracy' in a learning environment -- 6.7.1 Speed-Accuracy via Buck & Cheng (1993) -- 6.7.2 Speed-Accuracy via Vollichman (1993) -- 6.8 Learning curves in machining operations -- 7 Cost Models for Optimal Training Schedules 135 -- 7.1 Near optimal training schedules via experimentation: a military application -- 7.1.1 Problem description -- 7.1.2 Pilot study -- 7.1.3 Study objectives -- 7.1.4 Experimental plan -- 7.1.5 Partial experimental results -- 7.1.6 Improving the efficiency of the training schedule -- 7.2".
• catalog title "Human learning : from learning curves to learning organizations / by Ezey M. Dar-El.".
• catalog type "text".