A Comprehensive Guide to Engineering Product Development
What is engineering product development, and who are product developers?
There are challenging tasks for product engineers and product developers daily. Imagine creating a new product, enhancing an existing one, or innovating to address a specific need. Or you may have to adapt your product to ever-changing needs.
Fortunately, product design engineers don't work alone. Their teams are intertwined. Companies acquire suitable hardware and software tools and share best practices. Also, there are drives or constraints by market demands as well as regulatory and ethical considerations.
Are there consolidated paths from business goals to the final product?
Several ways and software options exist to assemble existing tools. The product development process and an associated concept, the engineering product development process, represent frameworks to help coordinate all the available resources for involved teams.
This article will discuss the product development process as a systematic process incorporating best practices for product engineering and other considerations impacting product design, such as upstream concept activities and product marketing. This process typically involves a multidisciplinary approach, combining branches of mechanical engineering, materials science and physics, design, and business principles.
The outcome is vital to bringing a product from concept to market.
This article will explore such a process, considering it's not an input-output box or a recipe but a vast collection of multidisciplinary, multi-objective activities relying on predictive analytics rather than practical experience.
AI assists product engineers in all phases of the product development process. Artificial intelligence can hone product engineers' expertise by merging experience and providing predictive models. While not a replacement for human expertise, it's a smart assistant deployable at any phase of product engineering, helping to design concept prototypes or providing more accessible product development services.
Product Engineering vs Product Development
Engineering product development and product development are two crucial processes required for creating successful products. Product engineering is a process that focuses on designing, developing, and testing a product to ensure that it meets the required quality standards and performance expectations. Knowledge of mechanical design, electrical or mechanical engineering, or other disciplines is needed in this detailed phase of the product development process.
Product development is closely related. But it encompasses a broader range of activities such as market research and conceptualization, with upstream decisions like: will the company launch a product with radically brand-new features or be an amelioration of one aspect of existing products?
Product development and product engineering processes are essential for creating innovative and successful products that meet customers' needs.
Thus, more than product engineering "vs" product development, we should think of product development and product engineering as enlarged and restricted versions of the same concept.
Key Stages in the Product Engineering and Product Development Process
We'll describe some of the mentioned processes to help teams in product design create innovative and successful solutions that meet the needs of end-users, major industrial customers, and regulatory organisms.
Conceptualization Phase and Industry Examples
The concept phase of a product incorporates business aspects consisting of identifying market needs and opportunities, generating and evaluating ideas, and defining the product's purpose, features, and target audience. The choices made in this state will influence the later product engineering phases.
In each industry, the concept phase is crucial for setting the foundation of a successful product by understanding market needs, generating innovation, and develop products that will resonate with the target audience.
In a certain sense, choices in this phase generate design concepts that are a legacy for product engineers in the later product engineering phase who should, for example, assess the product's structural integrity with tests or simulations for a car or develop the product prototype's desired user-friendly features.
Risks are lower when elaborating upon existing products and higher when the idea involves developing products from scratch. For instance, practical aspects could be solved thanks to customer feedback or requirements on the previous product to use as a "platform." Data collection and user feedback on past product features can help incrementally develop a new product version cost-effectively.
Product engineers and developers meet challenges with a new platform requiring more prototype development (physical or virtual) because they venture into a new, unknown design space in the product engineering process.
Automotive Industry Product Development Example
What are the main phases in the companies' product development phase, from business goals to product launch and user feedback? Without claiming exhaustivity, we'll analyze principles from the automotive industry including engineering product development approaches.
Market Analysis and Strategic Thinking Phase
This is the strategic thinking phase where business needs meet and comply with ethical principles such as sustainability.
First comes the market analysis of trends in consumer preferences and demands and the situation with competitors' offers. This must be coupled with environmental concerns and compliance with regulatory requirements, such as the demand for electric or hybrid vehicles.
This phase requires attention. It's now common knowledge that "cutting curves" has led to almost disruptive consequences in recent years, with scandals affecting global leading automotive companies.
Automotive Industry Product Development Example - Generate and Evaluate Product Ideas
When generating and evaluating product ideas, developers explore design concepts for fuel efficiency and alternative energy sources with other teams.
Moreover, Marketing, Sales, and Engineers brainstorm ideas for connected vehicles, integrating IoT and intelligent technologies and the need to prototype materials for specific purposes. It's also essential to consider innovations in materials for lightweight construction. In this phase, mechanical engineers and materials engineer interact, for instance, in the concept of new carbon fiber elements and testing them for crashworthiness.
But the fundamental question is, what will the product look like? Is the right product design appealing and resonating with our feelings? Virtual Reality tools coupled with Computer-Aided Design (CAD) or Computer-Aided Styling (CAS) allow teams to conceive vehicles and launch them virtually to test end users or attendees of specialized fairs. This will give a fair estimate of the final customer feedback. Customer requirements may be known, but testing the concept in practice in an ever-evolving market is essential.
Automotive Industry Example - Define the Product's Purpose, Features, and Target Audience
In this phase, teams create the product offers range, such as a family car, with or without sports or luxury version, and engine power range based on the above choices.
Design and Planning
Design and planning involve developing detailed product specifications to create a comprehensive design, including functional and aesthetic aspects. This should include planning the production process.
Testing and Reviewing Client Feedback
Some activities in this engineering product development phase are conducted thorough physical or virtual testing to ensure the product meets quality standards, client feedback, and making necessary adjustments.
This means to iterate on the design and product prototype as needed, with an iterative design approach.
Because of brand reputation and warranty return costs, the product must be cost-effective, but also, the product idea incorporates the concept of reliability. From the product prototype stage, the product should be tested for durability and ideally not contain unsustainable concepts of "programmed obsolescence."
Essential Principles for Successful Engineering Product Development
We'll focus on some principles and practical tools for cross-functional collaboration in manufacturing or services companies.
Cross-Functional Collaboration
Cross-functional collaboration fosters communication between all departments that are in charge to create a product or consider its manufacturing implications. It represents a vital part in teamwork and information sharing from concept to product release and maintenance down to obsolescence.
What software tools are available to foster collaboration in engineering product development? We'll see some in the next section.
Tools and Technologies in Engineering Product Development
We will briefly review modern software and hardware tools for product engineering and development, such as CAD, CAE, and 3D Printing.
Computer-Aided Design (CAD) Software
CAD allows for detailed 2D and 3D modeling of product designs and facilitates collaboration between teams. It can also be linked to VR and AR tools.
Simulation and Modeling Tools
CAE (computer-aided engineering) helps analyze and optimize product designs before prototyping them. The next revolution is using CAE data collection generated by engineering product development operations to democratize these costly and engaging tools, traditionally usable only by advanced aerospace or mechanical engineers.
Thanks to advances in Deep Learning, this is now possible, and all engineering product development teams can access predictive analytics with CAE quality but AI response speed and affordability. Risks involved in using "simplified" approaches are reduced by tuning AI prediction with high-quality CAE data.
Rapid Prototyping Technologies
3D printing and other rapid prototyping methods are essential for quick iterations in product engineering and enable faster testing and product design refinement.
Data Analytics and Artificial Intelligence (AI) for Product Engineering
Data analytics and AI are closely related concepts in product engineering since they're based on data coming from product engineering or end users.
The main tasks are to analyze data sets to gain insights into user behavior, market trends, and product performance. With data analytics, decision-making during various stages of product development is more robust, based not only on human intuition and general principles but also on collected data and can be shared between product engineers and other teams.
Key Takeaways
Engineering product development involves designing a systematic process from conceptualization to post-launch support.
Collaboration, user-centered design, risk management, cost control, and compliance are crucial principles that must be considered in product engineering.
To achieve this, it's important to utilize tools such as CAD software, simulation tools, project management software, and rapid prototyping technologies.
Data analytics and AI can be used for informed decision-making and to enhance user experiences and will help continuous improvement for successful product engineers.
