SYSTEMS ENGINEERING PRODUCIBILITY MODELING & SIMULATION NEEDS 

Dr. Al Sanders, Honeywell Aerospace, NDIA AMEC Chairman 

Brench Boden, AFRL ManTech, NDIA AMEC Vice-Chairman 

Producibility is routinely referenced as an important aspect to be considered in the systems engineering process, 

however it is usually neglected in the early conceptual and preliminary design activities because it is hard to 

quantify due to the lack of available analytical tools. And since producibility considerations are often neglected 

during these early systems engineering activities, a key customer input has not been included in the requirements 

definition process, the voice of the customer for manufacturing. The needs of this internal customer are equally 

as important as the external customer since they will be responsible for the long term production and profitability 

of the system that the development team is designing. Here the business needs of being able to meet the 

production cost, quality, delivery, and inventory targets must be considered as part of the trade study process 

when evaluating alternative design and industrial engineering concepts so that the impact of manufacturing 

capability, cycle time, test coverage, and yield can be taken into account and established as “design to” 

requirements similar to performance and weight targets. Figure 1 shows the results of a life cycle cost study that 

found 70% of the life cycle costs are locked in by the time conceptual design is completed when only 8% of 

actual development funds are spent1

. Clearly the largest, and only, opportunity to make step change 

improvements in affordability is in the front end of the systems engineering process as design concepts are being 

conceived and analyzed. 

Figure 1: Life Cycle Cost Commitment as a Function of the System Life Cycle

Currently, inadvertently “designed in” producibility issues impact defense system affordability through “hidden 

factory” mechanisms that are difficult to predict in early acquisition yet often have significant long term impacts 

on the manufacturing operations over the life of the product. For example, controlling inventory is vital to 

controlling factory operating costs once the system is fielded yet little consideration is given to the impact that 

early design and industrial engineering decisions have on these costs during early systems engineering activities. 

One of the primary drivers of work in process (WIP) inventory is the manufacturing cycle time required to 

manufacture the components and then build, integrate, and test the final product. Producibility problems often 

drive up WIP inventory due the additional cycle time, safety stock, and lead time buffers required to address 

unanticipated yield fallout and manufacturing inefficiencies associated with inadvertently “designed in” 

producibility issues that are impacting production rate and delivery performance. In addition these same 

producibility issues often impact the factory cost of poor quality (COPQ) metrics, with additional WIP associated 

with the “hidden factory” rework loops and associated quality control and oversight required to ensure products 

continue to meet design specifications that are on the ragged edge of producibility once they enter production.

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1 INCOSE “Systems Engineering Handbook: A Guide for System Life Cycle Processes and Activities”, version 3, edited by 

Haskins, C., INCOSE-TP-2003-002-03, June, 2006.

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Clearly producibility issues can have significant long term impacts on manufacturing enterprise operating costs 

due to the “hidden factory” rework, process inefficiencies, and overhead they introduce into the day to day 

production operations. Needed are the development of advanced simulation-based capabilities that can be used to 

analyze and “design out” producibility problems as requirements are being analyzed, designs are being conceived, 

and systems engineering “ility” trade-offs performed. These simulation-based capabilities would enable design 

and industrial engineers to identify potential producibility and manufacturing concerns during the “fuzzy” frontend of the design process where the flexibility exists to pursue alternative design and industrial engineering 

concepts that will satisfy both affordability and performance constraints. Currently simulation-based methods to 

predict system performance and functionality characteristics are routinely used to determine which alternatives 

are most viable early in the conceptual design process. However, comparable simulation-based methods suitable 

for the producibility analysis of large-scale complex weapon system components are severely lacking. 

Design For Manufacturability and Assembly (DFMA) has been commonplace in the automotive and consumer 

electronic sectors for several years now, but mostly consist of high level guidelines such as reduce part counts, 

simplify assembly operations, standardize parts, loosen tolerances, etc. If DFMA evaluation criteria do exist, they 

are usually in the form of checklists, or at best automated CAD-based rule checkers used to determine if the 

designer has adhered to recommended best practices or not. The limitations of these approaches are threefold: 

first they are only as good as the rules that are loaded into the checklists or software, second they are go/no-go 

and do not “quantify” the impact of not adhering to the rule, and third they are usually applied when the design is 

near final and enough information is available to answer all the checklist questions or run the CAD analysis, at 

which point it is too costly to implement significant design changes. For large-scale complex defense and 

aerospace systems where maximum functionality in the smallest and lightest package is the primary driver, it is 

quite common for numerous DFMA violations to occur as the design layout is being completed in order to meet 

competing performance, functionality, size, and weight objectives with producibility an afterthought.

The need for improved simulation-based capabilities and frameworks to integrate producibility and manufacturing 

considerations into early systems engineering activities was recognized the National Defense Industry Association 

(NDIA) in 2008, with a Joint Committee for Systems Engineering and Manufacturing (JCSEM) formed and 

chartered to identify current analysis capability gaps and define future analysis capability needs2

. The NDIA 

Manufacturing Division has recently added a fourth committee to its current structure aimed at identifying 

“engineering-based” approaches to enhance the affordability of weapon system development, production, and 

sustainment that is in the process of being kicked-off. The primary near term objective of the NDIA AMEC

committee will be to bring together subject matter experts in industry, government, and academia to help develop 

short and long term roadmaps for the following top six focus areas identified in the JCSEM M&S final report: 

• Systems engineering trade study and design decision methodologies

• System integration, assembly, and test modeling

• Electrical, mechanical, and assembly yield modeling

• Enterprise level supply chain design and analysis methods

• Quantitative DFX analyses including complexity characterization

• Should cost modeling including uncertainty and risk impact

The end goal of developing the roadmaps is to both spur government investments in new areas as well as provide 

use-inspired research guidance to university, government lab, and CAD tool vendors that is of high importance 

and interest to the defense industry. In addition, the complexity of the industrial base has increased almost lockstep with that of the physical weapon system, having evolved into a complex adaptive system of systems with 

characteristics that conventional supply chain management approaches fail to address. The overall vision is thus 

to define a roadmap for the development of advanced simulation-based producibility and supply chain analysis 

capabilities and frameworks that will enable true concurrent engineering and virtual prototyping of both product, 

!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! 2 Sanders, A., “Modeling & Simulation Investment Needs for Producible Designs and Affordable Manufacturing: Systems 

Engineering Implications”, NDIA JCSEM M&S Sub-Committee Final Report, February 2010.

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manufacturing, and industrial base design concepts through the use of advanced modeling and simulation and

systems engineering techniques.