Ford Motor Company Hood Development Process.
This DSM application was made to test the effectiveness of a DSM analysis to improve a highly developed iterative design process in terms of:
Reduction of product development lead time
Reduction of product development lead-time variation
As it is a process DSM, the nodes represent tasks in the design process. The edges represent dependencies between them. Each task in the design process was assigned a task volatility value, which is an indication of the probability of rework.
Node (task) weights:
EC(i) and EC(r) represent the initial and rework costs
ED(i) and ED(r) represent the initial and rework durations
Information variability (likelihood of input changing)
volatility: an indication of the probability of rework when the dependent task is executed without properly waiting for its input to finish. It’s value was determined using the information variability of the source (depended on) task and the sensitivity of the target (dependent) task.
References: Browning, Tyson R., and Steven D. Eppinger. 2002, November. Modeling Impacts of Process Architecture on Cost and Schedule Risk in Product Development. IEEE Transactions on Engineering Management 49 (4):428-442. Krishnan, Viswanathan, Steven D. Eppinger, and Daniel E. Whitney. 1997, April. A Model-Based Framework to Overlap Product Development Activities. Management Science 43 (4):437-451. Yassine, Ali A., Daniel E. Whitney, and Tony P. Zambito. 2001. Assessment of Rework Probabilities for Simulating Product Development Processes Using the Design Structure Matrix (DSM). ASME Design Engineering Technical Conferences, DTM-21693.
- ragraph.datasets.ford_hood.node_weights = ['EC(i) ($000)', 'EC(r) ($000)', 'ED(i) (days)', 'ED(r) (% of ED (i))', 'information variability']#
- ragraph.datasets.ford_hood.edge_weights = ['volatility']#