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  • Writer's pictureAnantaya Pornwichianwong

4 Critical Challenges in Manufacturing Industry

Nowadays, we entered the era of Industry 4.0, where industries are driven by advanced technologies like the Internet of Things (IoT), data analysis, and artificial intelligence (AI). These technologies have caused a significant transformation in manufacturing and other sectors, forcing companies to work hard to keep up with the rapid changes.

Companies need to elevate their production, accelerate operations, and maximize efficiency. They also have to deal with fluctuating and fast-changing consumer demands while carefully planning their production and managing their supply chains.

In this article, Sertis will guide you through four critical challenges that manufacturers are currently tackling. These challenges play a crucial role in determining a company's success. We will also propose solutions to these challenges, helping businesses confidently navigate through these transformations.

1. Depending solely on human workers may not be enough.

While human workers are important in manufacturing, there are areas where we can use automation and machines to our advantage. Embracing advanced technology can give your business a competitive edge.

Relying solely on manual workers has its drawbacks. It has limitations on the speed of production, making the business meet customer demands on time. It also raises safety concerns, as some machines can be dangerous for humans to work with. We should consider using technology for these tasks. Human errors can occur, especially in jobs that require high precision, like quality control. Sometimes, defects are so small that humans might miss them, or different workers might have varying standards.

How can we solve this problem?

AI and data can be significant tools to boost efficiency in our work. It can accelerate the production process to meet customer demands. We can utilize robotics and automation to handle dangerous and high-precision tasks. For example, we can utilize AI to improve the precision of the quality control process.

2. Demand Planning is more challenging.

In manufacturing, accurately planning for demand has become increasingly crucial. It affects how products are produced, resources are allocated, and supply chains are managed. This planning takes into account various factors, such as weather patterns, seasonal changes, customer preferences, geographical locations, and notably, the rapidly shifting trends in the market. Accurately predicting and planning for demand has become a new challenge manufacturers must overcome.

Inaccurate prediction and planning affect different stages of the process. It can lead to misallocated resources and even disrupt the production flow. Additionally, properly managing inventory becomes a challenge when the planning isn't precise. This can result in costly excess stock or stockouts.

How can we solve this problem?

AI possesses a remarkable ability to analyze vast amounts of data and forecast future trends based on historical information. Integrating AI into demand planning enables companies to anticipate demand and align production using real-time insights. This comprehensive understanding empowers companies to meet demands effectively, adjusting to changes promptly.

3. Production planning is more complex

Production planning is quite a complex process that holds a lot of importance in manufacturing. Producing an excess of goods can lead to surplus stock while producing too few can result in missed sales opportunities.

Effective production planning involves aligning resources with demand and optimizing processes. In today's interconnected global landscape, where a product's popularity can surge overnight and create sudden high demand, this task becomes even more vital. The manufacturing sector needs to be well-prepared to handle such scenarios.

There are several challenges in production planning. Inaccurate demand forecasting can lead to imbalanced production. Difficulty accessing real-time data on market trends, inventory levels, and supplier status can hinder the ability to adapt to changes, potentially causing delays or interruptions in production. Unexpected spikes in demand can strain production capacity, particularly that depend solely on humans, making the company unable to satisfy the needs of customers. This also occurs in the case of emergencies when the production level is not as expected. All these situations complicate production planning and heighten the risk of failing to meet customer needs.

How can we solve this problem?

By leveraging AI capabilities, companies can gather and analyze crucial data, including resource availability, demand trends, real-time market insights, and inventory status. These insights are useful for planning informed production scheduling and resource allocation. AI-driven plans can be adapted to accommodate real-time shifts, responding to the fast-changing world.

4. Dealing with a complex supply chain can be hard.

Dealing with a complex supply chain can indeed pose significant challenges. The supply chain encompasses various stages, including resource import, manufacturing, logistics, and product distribution, all of which are critical to a business's operations. Efficiently managing this intricate supply chain is essential yet challenging.

The challenges encountered in supply chain management are diverse, ranging from the complications of negotiating with suppliers, which can lead to delays and may disrupt production schedules, to substandard materials that compromise product quality. Additionally, logistics challenges, such as insufficient vehicles or inadequate warehouse management, can result in costly delays. Unforeseen events like natural disasters, adverse weather conditions, or traffic congestion complicate supply chain management as well. Ultimately, these challenges increase the risk of failing to deliver products to customers on time, hindering adaptability, and missing out on potential sales opportunities.

How can we solve this problem?

By leveraging a supply chain optimization solution, we can address this issue effectively. AI examines various aspects of the supply chain, including suppliers, inventory, logistics, and production plans, to identify opportunities for improvement, cost efficiency, and optimization. This ensures that the system can adapt effectively to changes.

Fully embracing the potential of data and AI is the recommended approach for manufacturers to overcome challenges, enhance operations, and allocate workers to more valuable tasks.

Learn more about solutions for manufacturing from Sertis

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