Can Product Testing Also Involve R&D? What BAE Systems Australia Shows About Technical Uncertainty as a Starting Point for R&D

Introduction

The Australian Government has long supported business R&D through initiatives such as the Research and Development Tax Incentive (R&DTI), encouraging businesses to address practical technical problems through research and experimentation. R&D does not necessarily require the creation of an entirely new technology. Improving existing products, equipment or systems may also involve R&D when technical outcomes cannot be known or determined in advance on the basis of current knowledge, information or experience, and resolving this uncertainty requires systematic, hypothesis-driven experimentation conducted for the purpose of generating new technical knowledge.

This raises a practical question: when does product testing go beyond verifying a known outcome and become part of an R&D process?

The Australian Government’s publicly available case study on BAE Systems Australia illustrates this point. The company undertakes R&D involving software, hardware, complex systems and algorithms, with relevant products undergoing laboratory testing followed by site testing.

For businesses involved in product development, system testing or engineering optimisation, the key question is how to turn an unresolved technical problem into a systematic R&D project.

Industry Background & Technical Challenges

For high-value equipment such as aircraft, corrosion can increase maintenance costs and affect normal operations if it is detected and addressed only after it becomes a problem.

Traditional maintenance approaches generally rely on periodic inspections and on-site testing. However, corrosion can vary in location and rate even under similar operating and maintenance conditions. Existing inspection methods and experience alone may therefore be insufficient to predict accurately when corrosion will occur, how it will progress or when maintenance should be undertaken.

BAE Systems Australia has worked with research institutions in the United Kingdom and Australia to better understand aircraft corrosion and investigate ways to detect and predict it before it becomes a problem. The project involves predictive algorithms and associated hardware, with potential applications in civil aviation, maritime and land-based equipment.

From Industry Problem to Research Problem

Publicly available information confirms that testing is an important component of BAE Systems Australia’s R&D activities, which also cover areas such as hypersonic technologies and electronic warfare. However, the available case material does not disclose the corrosion project’s specific hypotheses, experimental variables, algorithm details or test data. The following discussion therefore does not reconstruct BAE’s actual research process, but uses the technical challenge to illustrate how similar engineering problems could be investigated.

Identifying equipment problems, conducting inspections or optimising maintenance procedures does not, in itself, constitute R&D. The key is whether existing knowledge and experience are sufficient to explain the problem and determine the outcome. If they are not, further investigation may require a defined research question, a testable hypothesis and systematic experimentation.

Potential Research Question

For businesses seeking to detect and predict corrosion earlier, one potential research question is:

This involves investigating whether existing technologies can reliably identify early-stage changes, which factors influence the results, and why different technical approaches produce different predictive outcomes.

Potential Research Hypothesis

A business working in this field could hypothesise that inspection methods, system parameters and operating conditions affect corrosion detection and prediction outcomes.

This hypothesis could be investigated by systematically varying and comparing these factors to identify their influence on technical performance and assess the suitability of different approaches under different conditions. If results differ from expectations, further investigation would be needed to determine why and whether the hypothesis, technical parameters or experimental design should be revised.

Potential Research Factors

Relevant research factors could include inspection methods, equipment operating conditions, and data and analytical methods. Outcomes for observation and evaluation might include detection accuracy, consistency of identification and predictive performance.

For example, different inspection approaches could be compared under varying operating conditions to assess how changes in the data affect analytical results and the system’s ability to identify early-stage corrosion.

The purpose is not simply to increase the number of testing parameters, but to establish a clear relationship between:

Research Design & Methodology: How Can R&D Reduce Technical Uncertainty?

For similar engineering challenges, a systematic R&D process can follow a sequence of hypothesis formulation, experimentation, observation, evaluation and the drawing of logical conclusions, followed by further validation where necessary.

Initial experiments could be conducted under relatively controlled conditions to compare different technical approaches and identify factors that may influence system performance. Relevant parameters could then be varied systematically, with results compared across scenarios to examine their effects on detection and prediction.

The approaches could subsequently be validated under conditions closer to actual use to assess whether performance remains consistent. Where results differ from expectations, the reasons could be investigated and the hypothesis, parameters or experimental design adjusted.

The process can be summarised as:

The aim is not to prove a predetermined answer, but to progressively reduce uncertainty and develop an understanding of the relationships between technical factors and outcomes. In this way, a practical objective such as reducing equipment maintenance risks may give rise to a research project with a defined question, hypothesis and validation pathway.

Expected Outcomes & Industry Implications

For businesses working with complex equipment and engineering systems, R&D can generate value beyond the final product or technical tool. Ongoing experimentation, observation and analysis can help identify the factors influencing technical outcomes, validate the conditions under which different approaches are suitable, and generate new experimental data and technical knowledge to inform subsequent product improvements, system optimisation and technological upgrades.

The BAE Systems Australia case illustrates the role of testing in complex engineering R&D. However, testing and maintenance do not automatically constitute R&D. For businesses in mechanical equipment, maritime engineering, rail transport and advanced manufacturing, the key question is whether testing addresses an unresolved technical problem that requires systematic, hypothesis-driven experimentation.

Technical uncertainty can provide a starting point for research, but is not sufficient on its own to establish that an activity is R&D. What matters is whether a business can formulate a clear research question and testable hypothesis, conduct planned experiments, observe and evaluate the results, and draw logical conclusions to progressively generate new technical knowledge.