DESIGN OF EXPERIMENTS
"Those who ignore statistics are condemned to reinvent
it. Statistics is the science of learning from experience" - Bradley
Manufacturing Industry, some processes are so complex that even a very
experienced and competent engineer would not necessarily know how to identify
the best settings for your manufacturing equipment. In addition, most processes
are defined by multiple factors or inputs, each of which will change the
process output. How do we analyse the right setting for each factor? You obviously
cannot adjust one factor at a time and experiment in a disorganized way.
Experiments (DoE) provides an organization with a powerful tool that can help
them develop a model in a very practical, cost-effective, and flexible way,
allowing them to quickly identify the correct process settings.
systematic, rigorous approach to engineering problem-solving that applies
principles and techniques at the data collection stage so as to ensure the
generation of valid, defensible, and supportable engineering conclusions.
proved to be very effective in providing a greater understanding of any
process, leading to improvements in process yield, process performance, and
process variability. It also highlights opportunities for quality improvement.
It is therefore a powerful tool for process validation,
which is a requirement in heavily regulated industries such as the Automotive,
Aerospace, Pharmaceutical, and Medical Devices industries among others. For
example, the International Organization for Standardization (ISO) requires
process validation as a regulatory requirement. Design of experiment (DOE)
statistical methods will allow these requirements to be met with an efficient
use of resources (personnel time, machine time, materials, etc.) and at the
same time provides detailed analysis, gives information on reproducibility and
errors, and provides a predictive capability. Applying DOE reduces the size and
hence the cost of process validation trials.
day course will provide you with a comprehensive overview of the Design of
Experiments Process and how you can apply it to your organization.
workshop can also be delivered in-house as a stand-alone training workshop or
integrated into wider improvement activities.
We will be happy to discuss our Design of Experiments course in the context of your own business needs, so please contact us via email at email@example.com or phone +44 (0)28 9073 7950 for more information.