• Written by Sonali Subhadarsini, Product Manager

When the shift supervisor at a printing and packaging plant checks the maintenance log, they often notice a significant amount of downtime due to setup and makeready losses, which can be a major obstacle to productivity. The category manager, responsible for sourcing materials, may also struggle with quoting accuracy, as the cost of substrates and other supplies can fluctuate rapidly. As a result, the plant may experience substrate waste, which can be costly and inefficient. These challenges are inherent to the printing and packaging industry, and can make it difficult to implement productivity improvements.

Challenges in printing and packaging

The printing and packaging industry is characterized by job-shop economics, with heavy setup costs and frequent changeovers. This means that setup and makeready losses can be significant, as the plant must frequently switch between different products and production runs. Quoting accuracy is also a challenge, as the cost of materials and supplies can fluctuate rapidly, making it difficult to provide accurate estimates to customers. Additionally, substrate waste can be a major problem, as excess materials may be discarded or recycled, resulting in unnecessary costs.

These challenges can be particularly difficult to overcome, as they are deeply ingrained in the production process. However, by understanding the root causes of these problems, it may be possible to identify opportunities for improvement. For example, implementing a more efficient scheduling system could help reduce setup and makeready losses, while investing in better quoting software could improve accuracy. By addressing these challenges, plants can begin to unlock productivity gains and improve their overall efficiency.

Time saved vs time redeployed

When implementing productivity improvements, such as AI-powered tools, it is essential to distinguish between time saved and time redeployed. Time saved refers to the actual reduction in time spent on a particular task, while time redeployed refers to the ability to allocate that time to other tasks or activities. In the printing and packaging industry, time saved may not always translate to time redeployed, as the plant may still be limited by other factors, such as equipment capacity or material availability.

For instance, if a plant implements an AI-powered system that automates certain tasks, it may save time on those tasks, but that time may not be redeployed to other areas of the plant. Instead, the plant may simply produce the same amount of product in less time, without necessarily increasing overall productivity. To achieve true productivity gains, plants must be able to redeploy saved time to other areas, such as maintenance, quality control, or innovation.

Self-reported time savings

Self-reported time savings can be misleading, as they often overstate the actual effect of productivity improvements. This is because self-reported measures may not account for other factors that influence productivity, such as changes in production volume or equipment utilization. Additionally, self-reported measures may be subject to biases, such as the tendency to overestimate the impact of new technologies or processes.

To get a more accurate picture of productivity gains, plants should use objective measures, such as data from production systems or financial reports. These measures can provide a more nuanced understanding of the impact of productivity improvements, and help plants identify areas where further improvements can be made. By using objective measures, plants can make more informed decisions about where to invest their time and resources.

For more information on how to implement objective measures, plants can visit our website at www.asscherai.com to learn more about our AI-powered productivity tools.

Tasks worth removing first

When implementing productivity improvements, it is essential to prioritize tasks that are most amenable to automation or streamlining. In the printing and packaging industry, tasks such as data entry, reporting, and quality control may be good candidates for automation, as they are often repetitive and time-consuming. By removing these tasks, plants can free up time and resources for more strategic activities, such as innovation and customer service.

For example, a category manager may spend a significant amount of time comparing prices and availability of different substrates. By automating this task, the category manager can focus on more strategic activities, such as negotiating with suppliers or identifying new business opportunities. By prioritizing tasks that are most amenable to automation, plants can achieve the greatest productivity gains and improve their overall efficiency.

Limitations of AI productivity tools

While AI-powered productivity tools can be highly effective in certain contexts, they are not a panacea for all productivity challenges. In some cases, the implementation of AI-powered tools may not be feasible or cost-effective, particularly in plants with limited resources or infrastructure. Additionally, AI-powered tools may not be able to address certain types of productivity challenges, such as those related to equipment maintenance or supply chain logistics.

In these cases, plants may need to consider alternative solutions, such as process improvements or training programs. By understanding the limitations of AI-powered productivity tools, plants can make more informed decisions about where to invest their time and resources. For more information on how to determine whether AI-powered productivity tools are right for your plant, please contact us at www.asscherai.com/contact-us.