Beyond productivity: The 4 Aspects of Lean Budget Refinement

By Sharon Hsieh

First, Let’s Start With Smart Manufacturing

Industry 4.0 is an irresistible trend in the manufacturing industry, in order to meet customer needs and stay innovative. However, when manufacturers and this new idea are faces to face, the cost and complexity of it have deterred many of them. Is smart manufacturing necessary? What practical benefits can it bring? The answer is simple.

Smart manufacturing can produce better products at lower costs.

By introducing tools with IoT, data collection, and automation, we can provide significant agility to the production process. Today’s products are becoming more and more complex, due to the constant updating of features and components. In the past, customers put their focus on product quality, price, and delivery process. Now, they are also looking for “agility”, that is, how flexible can manufacturers respond to sudden changes in customer demand. Low volume but high variety manufacturing feature is forcing companies to transform.

“Agility” is listed as an important core capabilities in Industry 4.0 (Source: McKinsey  )

Cost reduction comes from:

1. Ensure product quality in each stage of manufacturing

One of the major cost factors to factory productions is defective unit. Smart manufacturing monitors the quality of products in the production process and eliminates errors that are not aware by humans. Detects problems as early as possible and reduces the chance of producing defective products and reproduction.

Unlike manual monitoring, manufacturers can see the real key impacts hidden beneath the surface by using AI to gather data. These additional metrics and insights can help identify quality variation caused by humans, machines, or the environment and resolve problems more quickly.

Having higher quality products achieves the ultimate goal in manufacturing industry – “increasing brand value”. Delivering well-made products, not only enhances customer relationships but also subsequent repair costs and the chance of product recalls. Smart manufacturing proactively prevents errors from occurring, ensures delivery quality, and serves as a gatekeeper for the production line.

2. Predictable inventory

The cost of maintaing the inventory is often forgettn by the compaies while evaluating the total cost of production. These costs include taxes, inventory service costs, insurance, depreciation, etc.

By utilizing artificial intelligence, manufacturers can simplify and visualize intensive assembly line information, assess production status, and reduce over-ordering and under-ordering of materials. At the same time, with higher yields, factories no longer need to keep more raw materials in stock in case of product problems that require remanufacturing. Reduction in inventory reduces space, management costs, and other relative costs.

3. Advanced deployment, smooth production

Smart factory deploys high-level technology that gathers useful information about equipment performance and operators’ movement, helping factories achieve higher equipment utilization, lower production downtime, and improve SOP.

The productivity of an assembly line will be affected when the machine is down. Factories not only need to repair the machine but the downtime also causes delays in production and additional costs to the factories. However, data analysis help prevent this in advance. By evaluating the machine by its performance with real-time alerts, factories can take action immediately to fix the problem, meanwhile, avoid futher damage.

What’s more, long-term data collection is useful for line balancing and SOP analysis, analyzing the root causes of inefficiencies, and identifying what can be improved in each station or process.

These improvements can help reduce maintenance costs, improve equipment availability, personnel efficiency, and more, leading not only to better continuity of operations but also to increased output and optimized production performance.

4. The route of data movement

By analyzing long-term data movement, we are able to link information in the different production processes by data collection, integrate various applications, and the assist of AI. Which means we are able to analyze the production status in all aspects.

Manufacturers can go back to any stage of the assembly line and compare the status of stations in different time slots as if they have a complete factory history timeline to understand the present position and predict future development.

Data-driven operational strategies enable companies to utilize resources more effectively, save costs, and develop production strategies. Through fully integrated end-to-end management, companies will increase business flexibility and, more importantly, “create new value in the industry.” Transforming operations will provide companies with a sustainable competitive advantage in the industry.

Companies that adopt AI have seen cost reductions in “service operations,” “manufacturing,” and “product/service development” that also outweigh “profit increases.”

Reducing cost, and then?

Smart operation and management

Building smart factories and upgrading operations management strategies enable an agile and dynamic business environment. Extra profits from cost reductions can be used as future budgets and accelerated investment in future innovation.

Building smart factories and upgrading operations management strategies enable an agile and dynamic business environment. Extra profits from cost reductions can be used as future budgets and accelerated investment in future innovation. Together with AIoT and Al analysis, well-develop the technology platforms, and eventually move forward towards lean manufacturing. the core value of Industry 4,0 is not only about digitalization but also about creating new value for the future with improved partnership in the industry.

Make your first step, create the innovative core of the factory

PowerArena creates computer vision AI that helps improve assembly line performance. The deep-learning AI records the movements of operators and collects large amounts of data, bringing you clear information and detailed control of the entire manufacturing process. By enabling production digitally; and with the assistance of AI, manufacturers are able to allocate production costs into different parts of budget planning, eventally achive the goal of lean manufaturing.

Source:https://www.techtarget.com/searchcio/tip/6-tips-for-digital-transformation-budget-planning / https://www3.weforum.org/docs/WEF_The_Global_Lighthouse_Network_Playbook_for_Responsible_Industry_Transformation_2022.pdf

Read More:

Applied AI&Digitial Transformation

From Low-code to No-code: An AI democratization

635