How can you ensure quality product engineering without sacrificing speed?

Just as important as defining clear and realistic goals is that they are measurable - ideally quantitatively (scrap reduced by x %, first time right y%) but if that is not possible with a qualitatively (e.g., percentage of users who deem the product/ system easier or much easier to use > x % or net promoter score > y %). You may find that by defining how something is measured difference in understanding and underlying assumptions of stakeholders are revealed.

I would like to add on ensuring quality engineering products that 1.Human Interference in concerned process need to be replaced systematically by removing NVA activities,implementing lean practices to make process robust. 2.Implementong new method,technology,RFT to ensure that part produced is as per customer specification.

Analyze the negative reviews (3-Star + below) from your Customers & Customers of competitors, by demographics, if possible to determine real Customer pain points and desires. 3-Star reviewers will tell you what you need to do to get beyond average to delight. For example, "I would love if you just ...."

Garantir uma engenharia de produto de qualidade sem sacrificar a velocidade é um desafio, mas é possível! Algumas estratégias incluem: Foco na eficiência, automa??o inteligente, itera??o rápida, testes contínuos, colabora??o eficaz, Prioriza??o inteligente e aprendizado contínuo.

In some projects, there is uncertainty regarding what the customer actually wants and how one might implement them. Yet, sometimes, a multi-phase waterfall approach with few agile elements or select phases in which the team adopts an agile approach (and mindset !) are more efficient. The Cynefin framework and Stacey matrix are valuable tools to determine what methodologies and frameworks should be utilized.

Use the 7 Ways & the 3P Production Preparation Process to generate ideas. Combine ideas to optimize design to meet top Customer desires. Perform a concentrated risk analysis on the Final 7 Ways to remove. reduce or replace high risk circumstances.

Using DOEs (Design of Experiments) is a great way to optimize product variables. It allows you to systematically vary multiple factors at once, identifying the best mix of variables to achieve a desired outcome, saving time and other resources. This is incredibly useful in product design and root cause analysis, allowing for identification of quick iterations and alterations of product specifications. It helps if you have a previously existing version of that product in the market, as data from the existing product may provide relevant insights into the new product being created.

Rapidly prototype or mock up, get the prototype into User Groups & beta testing, analyze & record Customer interactions (including verbal/nonverbal language, facial expressions, side comments), then iterate. It doesn't matter if prototypes are not fully operational as long as the Customer can understand the goals of ultimate development. It's great if you can get a Consumer Focus lab with Facilitator & hidden control room to collect all the interactions from all angles and hidden microphones.

It'll be interesting to see how AI affects the product quality space, both on the consumer side and the manufacturing side. We already see AI able to sift through Amazon product pages and succinctly summarize past consumer remarks for a potential new consumer. As manufacturing side AI tools are further developed, we should gain significant data (and recommendations even from the AI?) to improve upon products universally.

It's great if you can get a catalog of Best Practices for comparison, even it's from a different industry. It's the deep thought that counts. Every product iteration should have a living set of FMEAs (Design, Process, Manufacturing, User Interface/Experience) that establishes a history of risks and shows progressive design improvement iteration; a.ka. Lessons Learned. This is painful to start from scratch, but is a tremendous tool so you don't have to recreate unlearned painful experiences.

If not using standardized test methods, make certain the test methods used are validated before utilizing them in any development work or transfer.

Quanto mais cedo um time de engenharia entra na discuss?o de novas features mais chance tem a entrega de entrar com boa qualidade. Os chamados "corner cases", gaps funcionais em boa parte podem ser evitados se uma boa discuss?o fosse feita no início da discuss?o entre as áreas de negócio, produto e tech. Com mais pontos de vista na mesa mais situac?es fora do "caminho feliz" s?o vistas e mitigadas ainda em fase de desenho. Quanto mais "shift left" for feito na detec??o de algo indevido ou n?o tratado, mais barato se erra e mais feliz fica o cliente.