Knowledge Aware Engineering

Knowledge Aware Engineering is a fundamentally new approach to managing technical knowledge. It replaces the traditional, passive ‘reference shelf’ model with an integrated, active knowledge system that directly influences technical decision-making and analysis. Knowledge Aware Engineering can help your organization:  

  • Increase productivity of technical workers;
  • Prevent recurring engineering errors and promotes quality;
  • Retain technical know-how, independent of people; and
  • Ensure consistent, multi-location engineering processes, outcomes.

Engineers using Knowledge Aware Engineering do not sift through document repositories and databases in hopes of finding something useful.  Instead, essential learnings and technical memory are allocated [1] directly into existing work-flows, giving engineers exactly what they need, when and where they need it, to make qualified and robust decisions.

 

Technical_Memory

 

The free flow of complete and relevant know-how into existing processes establishes three fundamental Knowledge Aware Engineering value pillars:

  • Certainty in knowledge re-use
  • Continuous product and process validation / verification / evaluation
  • Closed-loop enterprise learning and knowledge sharing

Promoting continuous in-context knowledge allocation and influence makes your company’s existing work-flows knowledge ‘aware’– hence the name Knowledge Aware Engineering.

 


 

How Knowledge Aware Engineering Works

Instead of using documents as a vehicle for conveying knowledge, Knowledge Aware Engineering uses purpose-built encapsulations of active knowledge: knowledge packets. These knowledge packets are granular units of know-how that are automatically allocated into work flows. The process of knowledge allocation involves calculating what specific know-how is needed for a particular task or decision, and then pushing the knowledge into the technical workflow in an automatic, low-effort, integrated way. Importantly, allocation does not require the end-user to perform a search of any kind.

Knowledge Aware Engineering has two component cycles, Continuous Knowledge Capture and Continuous Verification.

 

 

Communities of Practice (CoPs)

Auros engages the workforce through a concept called ‘Community of Practices’ (CoP). CoP’s leverage and align with the naturally occurring ‘communities’ that exist in your company. Each CoP is comprised of people with shared work experiences and areas of expertise, for example ‘product design’, ‘manufacturing’, ‘process x’,— any kind of knowledge. Within Auros, ‘CoPs’ provide the framework for bottom-up, organic knowledge management.

 

Knowledge Packets (K-PACs)

The ‘Knowledge Packet’ (K-PAC) is the fundamental unit of knowledge in Auros. It is important to emphasize that the K-PAC concept is purpose built for representing knowledge and is fundamentally different from a ‘document’. Like atomic elements, K-PACs in Auros combine and recombine, and are pushed out in a complete set of relevant, accurate knowledge to users in context. Knowledge Packets are delivered and evaluated as impactful decision support within everyday workflows, driving continuous improvement within all phases of engineering.

Acquisition

The Auros ‘Knowledge Aware Engineering’ process has two mutually dependent sub-processes: ‘Acquisition’ and ‘Re-Use’. In the ‘Acquisition’ phase, users are engaged in the process bottom-up, organic knowledge capture. Auros CoPs and K-PACs are fundamental innovations that support this process.

 
 

Re-Use

The Auros ‘Knowledge Aware Engineering’ process has two mutually dependent sub-processes: ‘Acquisition’ and ‘Re-Use’. In the ‘Re-Use’ phase, knowledge is delivered to users without having to leaving their natural workflow. Knowledge re-use drives better behaviors and better results. Auros Assessment Controls’ and ‘Issues Mgt’ integrate into natural workflows new and fundamental capabilities which enable unprecedented levels of knowledge re-use.

Assessment Control

The Auros ‘Assessment Control’ provides a rich set of features that process, apply, and evaluate K-PACs within a given workflow. By evaluating/applying K-PACs from within your company’s natural workflows, processes become robust, consistent, and efficient across organizational divisions, time, and/or geography.

 

Issues Management

The Auros Issue Management system provides efficient and flexible problem solving tools. Importantly, Auros Issue Mgt is integrated into the Assessment Control process allowing problems to be resolved in the context where they are encountered. Issues Mgt can track simple ‘tasks’ or full problem solving techniques like ‘8-Ds’ (and everything in between).

Auros Issue Management also has advanced feature sets. For example, with Auros Issue Mgt Proximity Search’, recurring issue are automatically identified, providing a basis for continuous improvement and closed loop learning.

  • Continuous Knowledge Capture – Self-regulating communities who share work, process or technical know-how, create and share knowledge packets with each other and with other communities on an ongoing basis[2].
  • Continuous Verification – Assessment controls are how knowledge packets are allocated to users within their natural work-flows, where they are used for efficient and continuous verification, problem solving, and reporting.

Knowledge Aware Engineering is not a distant point on the horizon. Enabling technologies like the knowledge packet and assessment control are commercially available now. Early adopters have demonstrated and measured enterprise-wide success. Their measured success includes multi-year patterns of increasing levels of demand-driven adoption of Knowledge Aware Engineering and organic style growth[4] of technical memory. Leaders in Knowledge Aware Engineering have matured their deployments into global capabilities that improve all phases of engineering.

 


 

The Knowledge Aware Engineering ‘Virtuous Cycle’ and the Learning Organization

The virtuous cycle of Knowledge Aware Engineering is like a flywheel. Apply some energy to start the wheel in motion. Gather knowledge into packets and apply it into the work-flow. As technical memory is used and reused, it becomes more visible and the workforce becomes engaged. More energy is imparted to the flywheel, accelerating production of additional technical memory and reuse visibility.

 

Virtuous_Cycle_Flywheel

 

When a critical mass of visible reuse is reached, the flywheel produces more energy than it consumes, becoming a self-sustaining ‘virtuous cycle’. By internalizing the value-generating process that fuels the growth of technical memory, an organization transforms into a learning organization. [3]

 


 

Next Steps

As technical processes become ever more model-based, the need for Knowledge Aware Engineering will intensify.  These emerging model-based technical processes will rely upon real-time knowledge allocations to perform their function (e.g. ‘Smart CAD’).  Establishing proficiency in Knowledge Aware Engineering today may be the most important strategy for achieving success tomorrow. If you’re interested in learning more about Knowledge Aware Engineering, download the complimentary Knowledge Aware Engineering White Paper, or access the Auros Document Vault for additional resources.

If you’re interested in receiving a complimentary live demo, click here, or you may contact us directly at info@aurosks.com or (313) 289-3972.  

 


 

[1] In the same way that funding or budget is allocated to a given project to meet the project’s specific funding needs, knowledge can be allocated to a project to meet the project’s specific knowledge requirements.

[2] The knowledge packet based process for knowledge capture replaces existing document based strategies while reducing the aggragate cost of knowledge capture.

[3] “A learning organization is an organization skilled at creating, acquiring, and transferring knowledge, and at modifying its behavior to reflect new knowledge and insights.” – David A. Garvin, HBR.

[4] The hallmark of organic style growth is a continuous and smooth curve of increasing (over time) levels of activity, increasing number of users, and increasing number of knowledge packets. ‘Growth’ is organic in the sense that it is occurring naturally through bottom-up demand and not through top-down edicts which generally result in discontinuous or negative growth curves.

 

Facebook
Google+
Twitter
YouTube
LinkedIn