Drive rational decisions with data-driven analyses.
Concurrent Product Development uses the proven, data-driven business analytics and diagnostics tools of Six Sigma to guide continuous process improvement initiatives and rational decision making in organizations.
In general, existing process and product improvement initiatives are organized using the DMAIC (Define, Measure, Analyze, Improve, Control) methodology. New processes and products are designed using the DMADV (Define, Measure, Analyze, Design, Verify) approach. Both methods are similar in that they are heavily dependent on statistical analysis of objective data to drive measurable improvements within organizations.
What are the benefits?
- Improved capacity, production rate, process yield, quality and reliability
- Reduced lead time and faster turnaround time
- Reduced costs resulting from process waste and variation, defects, rework, customer returns and field failures
Specific areas where we can help
- Process definition using VSM (value stream mapping) and SIPOC (Supplier, Input, Process, Output, Customer) visual tools
- Process performance characterization and capability indices, including process control limits and definition of upper/lower spec limits
- Process optimization and troubleshooting using DOE (Design of Experiments), controlled and screening experiments, multiple response optimization and before/after comparisons using hypothesis testing
- Process modeling using regression analysis and data fit characterization
- Experimental design including bold/iterative strategies, control group, replication, randomization, and “blocking” and definition of sampling plans and sample size calculation
- Product life evaluation, field reliability, and determination of MTBF (mean time between failures)
- FMEA (Failure Modes Effects Analysis) and risk ranking using CN (criticality numbers) and RPN (risk priority numbers)
