Fixing Growth Pains in Manufacturing: New Solutions Can Change the Game for New Product Introduction

September 21, 2021

Manufacturing is a competitive sector. With ever-growing demand for more quality and complexity, product innovation is the battle-ground where market share is gained or lost. Engineers need to find better and faster ways of bringing new products into series production. Rethinking existing product introduction (NPI) strategies can help products to market faster.

As a general rule of thumb, properly overhauling NPI plans can lower overall development costs, enhance risk management, and improve the quality of your products. Yet, if executed with misguided business objectives, optimising processes can actually stifle innovation, since new designs can become less of a priority when the team focuses on meeting product launch deadlines and other requirements.

It’s only by finding the right balance between new technologies and smart business objectives that companies can manage demand for new products. Here is a closer look.

What Is New Product Introduction (NPI)?

Classical NPI is easy. Series of processes are used to outline the steps needed to develop and produce a new product. A typical NPI process includes six steps:

1. Define goals and risks

2. Determine feasibility

3. Develop and prototype the product

4. Validate the manufacturing process

5. Implement the manufacturing process

6. Evaluate the process

Providing a team with a clear set of guidelines allows them to focus on each stage of the NPI process. Team members tend to gain a better understanding of the target audience and find ways to improve product quality. In today's market, only keeping to the classical process means businesses run the risk of falling behind the competition in both speed and efficiency.

Taking advantage of the following cutting-edge technologies will ensure you give your company the best chance at innovation:

Streamline Prototyping with Digital Twins

Digital twins streamline the creation and testing of prototypes. Engineers can develop digital prototypes to test a wider range of design options before producing first samples. Developing a virtual prototype reduces costs and saves time.

Although complex to build and manage, the ability to predict quality outcomes and simulating production processes before implementation means new products can be adapted to manufacturing situations without the need for labour and material intensive iteration processes. Simulations help with the decision-making process, allowing engineers to detect limitations or find ways to improve the product.

Use Digitisation to Improve Manufacturing Processes

Along with streamlining the prototyping process, digitisation allows manufacturers to streamline other manufacturing processes. The availability of empirical production data inside software can automatically generate real-time analysis and reporting of product progress, in the meanwhile notifying engineers of potential risk areas and root causes for issues. This level of automation frees up engineer time, letting them focus on making data-based decisions rather than analysis.

Using big data may also uncover solutions for improving the efficiency of scheduling, maintenance, and individual manufacturing processes. For example, new quality assessment processes can automatically identify the optimal batching sequence for production, so that plant utilisation can be maintained at optimal with new products along existing products.

Digitising manufacturing processes also makes it easier to analyse each process to detect and eliminate bottlenecks. Each improvement may result in fewer defects, lower costs, and faster production runs.

Use AI and Machine Learning for New Product Forecasting

Product development is often a time-consuming process. By the time that a manufacturer gets a product to market, conditions may have changed.

AI system can analyse the market and assist with new product forecasting. Manufacturers can accurately predict the market conditions for the product launch. Instead of overproducing or underproducing a product, you can anticipate demand and adjust manufacturing processes accordingly.

More accurate product forecasting leads to many advantages during new product introduction. Forecasting helps limit waste and reduces inventory costs. It also reduces the occurrence of delays due to supply chain issues, which can also be addressed using additional AI solutions.

Boost Availability with AI-Assisted Supply Chains

Before you can introduce a new product to the market, you need to bring it to series production. Depending on the speed of your NPI process, your supply chain may not be ready to accommodate your production run. You need to ensure that supplies and materials are available to meet your needs.

AI assisted logistics systems help manufacturers maintain optimal stock levels and increase operational efficiency. However, AI-powered supply chains may also decrease costs and increase revenue.

According to a survey of manufacturing executives, 61% of manufacturers experience decreased costs after implementing AI for their supply chain management. AI gives managers more information for better decision-making, allowing them to predict bottlenecks and gain complete visibility of the entire supply chain.

Track and Analyse the Success of Your New Product Launch

AI and ML solutions continuously bring additional value after the launch of your product. You can use software to track and analyse every aspect of your product launch, including total costs, profits, and sales volume.

Tracking products after launch provides AI and ML software with more data. The data obtained helps increase the accuracy of future AI-driven decision-making. For example, the success or failure of a recent project informs the AI software when completing product forecasting on future projects.


Using the latest technologies gives your company greater flexibility to design and manufacture new products. Implementing artificial intelligence and machine learning solutions helps:

●      Streamline prototyping using digital twins

●      Develop more efficient manufacturing processes

●      Improve the accuracy of product forecasting

●      Increase the efficiency of the supply chain

●      Track the success of your new product introduction (NPI)

Integrating new technologies with new NPI processes is integral to an industry 4.0 vision of every manufacturer. Before implementation, organisations need to take their time and learn more about what is available and what are their individual business needs.

If you want to harness the power of AI and ML for your new product introduction plan, consider partnering with digitisation and automation experts.

Feel free to also check out our other posts:

Combating Small-Batch Manufacturing with Technology

Manufacturing Process Analysis: Starting Points for Fast Improvements

Fast Track to Industry 4.0: Low-Code Development in Manufacturing