This presentation was held at the 2020 NAFEMS UK Conference "Inspiring Innovation through Engineering Simulation". The conference covered topics ranging from traditional FEA and CFD, to new and emerging areas including artificial intelligence, machine learning and EDA.

Resource Abstract

Simulation Data Management (SDM) is a software solution which enables Professional Simulation Engineers to find information, run simulation applications and store results. An SDM solution records and displays the Digital Thread and records of engineering simulations. It replaces record keeping in notebooks and file storage on shared drives with structured digital records in a secure, searchable repository. SDM has been pioneered by high performance Automotive and Aerospace OEMs and Tier 1 suppliers over two decades.

Organisations typically start the transition to the management of simulation data in an SDM repository when the complexity and size of their simulation data-sets make it no longer practical to manage them using manual record keeping. SDM is usually deployed by organisations which use numerical simulation as the basis for engineering decisions with significant economic or safety consequences.

Capable SDM solutions have proved highly effective at these leading organisations to ensure that the right data has been used and to assure simulation quality. SDM provides increased confidence in simulation results by the capability to display the graph, or digital thread, which traces the simulation process from the initial simulation request as a sequence of process steps leading to the final results. SDM projects offer a good ROI to medium sized and large simulation organisations, but are inherently costly and time consuming due to the diversity of simulation applications and processes and a lack of experienced SDM implementation staff.

SDM solutions support process improvement initiatives which typically take the As-Is processes recorded by the SDM solution as the starting point to formalised, standardise and optimise processes. SDM solutions have been enhanced to provide flexible simulation process automation and are often referred to as SPDM solutions.

Successful adopters of SDM have reported substantial gains in engineering throughput through the elimination of laborious, non-value-added data management tasks, increased reuse of data and knowledge as well as the progressive automation of repetitive tasks. It is important to emphasise that the most successful SDM solutions support numerical experimentation by skilled analysts; they have not sought to prescribe inflexible processes. It is a common misconception that SDM solution seek to enforce prescriptive workflows, a typical PDM approach for CAD data, which has proved inapplicable to simulation management for experienced analysts.

Successful SDM projects have been characterised by clear objectives, a focus on delivering value to the analyst and the organisation, and achieved through the implementation of a mature, capable SDM solution by a specialised and experienced services team. However, overall adoption of information systems to manage simulation data by engineering analysts is still pitifully low at 1%-2%, as evidenced in the SimBest report.

Complementary approaches for managing limited subsets of simulation data have emerged. Analysis Planning and Reporting is an important technique applicable to organisations of all sizes and is valuable in its own right and to prepare for an SDM deployment. Simulation-enabled PDM is used for the management of meshing and of simple datasets created in CAD-embedded applications by design or manufacturing engineers.

SDM is still an emerging domain with proposed solutions of widely varying capability and maturity. Solution selection needs to focus on capabilities, ergonomics, ease of adaption and on openness to manage the wide variety of simulation software found in most organisations. Selection should be based on practical testing of solutions’ capabilities with your applications, data and processes and include a Proof of Concept.

Un-successful projects to implement solutions to manage simulation data have been characterised by attempts to implement inappropriate or immature IT solutions by service teams without experience of simulation or of managing simulation data and a disregard for the specific needs of the simulation community.

This presentation provides a summary of the key points to consider in order to succeed with a project to manage your simulation data and enable the transition to simulation driven development.