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Does the introduction explain the objective of the research presented in the preprint?

Partly

Yes, though not in great detail. The introduction sets up why the research was done: automotive companies are under pressure to improve time-to-market, and Lean Thinking is increasingly being applied to product development to cut waste and costs. It then gives one sentence on the actual objective, which is to propose a Lean Product Development framework to understand how Lean Thinking impacts manufacturing processes in an automotive company. It also mentions the specific product being studied (a High Voltage Air Heater for a Battery Electric Vehicle) and the company's shift toward electrification, which gives some useful context. What it doesn't do is spell out concrete goals like reducing lead time or improving process efficiency.

Are the methods well-suited for this research?

Somewhat inappropriate

Action Research makes sense here because one of the researchers was embedded in the company, working directly with the engineers. That kind of hands-on involvement is actually well suited to a process improvement study like this, where you need people to open up about how things really work rather than how they're supposed to work on paper. The tool is also a reasonable choice for mapping a product development process, and the team brought in people from multiple departments to build the value stream maps, which adds credibility. Where it falls short is that the lead time and efficiency numbers rely heavily on team estimates rather than hard data. The future state figures are also more of a projection than something that was actually measured after the changes were implemented. And since it's a single product at a single company, you can't really generalize the findings beyond this specific context. The authors are aware of some of this, but it still limits how much weight you can put on the conclusions. So the methods are solid enough to tell a convincing story about what happened in this particular case, but not quite rigorous enough to make broader claims.

Are the conclusions supported by the data?

Somewhat unsupported

The core findings hold up. The lead time and efficiency numbers are calculated clearly and the logic behind them is easy to follow, so the main conclusions do make sense given what was measured. The problem is that the future state numbers are largely based on estimates and projections, not on actually running the improved process and seeing what happens. So when the paper says LPPD made a significant positive impact, that's only partly backed by real observed data. It's more like a well-reasoned prediction than a proven result. The authors don't really flag this distinction, which makes the conclusions sound more definitive than they probably should.

Are the data presentations, including visualizations, well-suited to represent the data?

Neither appropriate and clear nor inappropriate and unclear

The figures that are there, like the waste comparison table and the workload graphic, do their job reasonably well. The formulas for lead time and process efficiency are presented clearly enough to follow. But the two most important visuals in the paper, the current state and future state Value Stream Maps, are basically unreadable. They're blurred or shown at such a small scale that you can't actually see what changed between the two states. For a paper that is fundamentally about value stream mapping, that's a pretty significant gap. You're essentially being asked to trust the numbers without being able to see the work behind them. So it's not that the presentation choices are wrong in principle, it's more that the execution leaves the reader without the visual evidence they would actually need to evaluate the findings.

How clearly do the authors discuss, explain, and interpret their findings and potential next steps for the research?

Somewhat clearly

The authors do a decent job of connecting the findings back to the original goals. They explain what the lead time and efficiency improvements mean in practical terms, acknowledge that the team still needs to build familiarity with tools like QFD and VSM, and are reasonably candid that LPPD is still in its early stages at this company. The next steps are also spelled out, things like continuing to follow up on the improvement proposals, maintaining a continuous improvement mindset after the project ends, and aiming eventually for a zero defect process. That's useful. Where it falls a bit short is depth. The discussion doesn't really dig into why certain problems occurred or what specifically made the improvements work. It reads more like a summary of what happened than a genuine reflection on what was learned. For a study using Action Research, which is supposed to emphasize learning and reflection, you'd expect a bit more of that critical thinking to come through in the discussion section.

Is the preprint likely to advance academic knowledge?

Moderately likely

The paper does contribute something real. Lean thinking in product development is still a relatively young area compared to lean manufacturing, and there aren't that many published case studies showing how it plays out in practice at an automotive company. The combination of LPPD workshops with VSDiA is also a fairly specific application that others working in similar contexts could learn from. That said, it's hard to argue this moves the needle much academically. It's one product at one company, the data relies heavily on estimates, and the tools used (VSM, LPPD, QFD) are all well established in the literature. The paper is more of a "here's how we applied existing methods and it seemed to work" story than something that introduces new theory or challenges existing thinking. It's the kind of paper that's useful for practitioners looking for a real-world example, but probably won't be heavily cited by researchers building on it.

Would it benefit from language editing?

Yes

The paper is readable and you can follow the argument, but there are enough awkward phrases and grammatical slips throughout to be noticeable. Things like "the undertaking needs to be scoped", "this requires a robust product design which allows the application of stable and lean processes", and some sentences that just run on a bit longer than they should. A light edit would make it flow much better and come across as more polished.

Would you recommend this preprint to others?

Yes, but it needs to be improved

It's a genuine case study from inside a real company, which is always valuable, and the results are interesting enough to be worth reading. If you're working in lean product development or trying to understand how LPPD gets applied in practice, there's something useful here. But before it's ready for wider circulation it needs cleaner language, better quality figures (especially the value stream maps, which are the whole point of the paper), and a more honest separation between what was actually measured and what was projected. Those aren't fatal flaws, they're fixable, but right now they hold the paper back from being as credible as it could be.

Is it ready for attention from an editor, publisher or broader audience?

Yes, after minor changes

The core content is there and the paper has a clear structure. What it needs before going to a publisher is a language edit, readable versions of the value stream map figures, and a clearer acknowledgment that the future state results are projections rather than measured outcomes. None of that requires rethinking the research itself, just tightening up the presentation.

Competing interests

The author declares that they have no competing interests.

Use of Artificial Intelligence (AI)

The author declares that they did not use generative AI to come up with new ideas for their review.