The Risks for Factory Owners of not Embracing Industrie 4.0 Models
7 Sep, 2019
Supply chain and logistics management are the factors that determine how efficient a factory is run. According to Industry Week, the greatest challenge factory owners face involves locating inventory and inventory accuracy. Other issues of note include material handling and transportation through shop floors. These pain points have led to material waste, downtime, and inefficiency across the world's factories. In an Industry where on-time delivery is key, these inefficiencies lead to huge losses. Manufacturers generally have to deal with 800 hours of downtime yearly and in the automotive industry, the monetary value of these losses is approximately $22,000 per minute.
The real and perceived costs of inefficiencies to factory owners also include loss of customers and brand dilution. This is why global factories invest top dollar on logistics-related R&D. Today, the research is centered around integrating Industrie 4.0 business model and the results are encouraging.
This article will discuss:
Some Industrie 4.0 business models factory owners can leverage.
How overlooking Industrie 4.0 models will affect the competitive edge of factories.
The advantages of embracing Industrie 4.0 to ease supply chain and logistics problems.
What risks do factory owners face by ignoring Industrie 4.0, and how can they stay competitive?
In factories dealing with perishable goods, statistics show that 64% of wasted goods are due to operational challenges. These challenges include; over-supply and inventory inaccuracies. Moving to the unbelievable but factual, not knowing where inventory is located has also been responsible for waste.
At the heart of these losses are data collection and management problems. This is due to the manual collection of data and human error. In production cycles, human error is still the leading cause of data loss and misuse. According to Dell, 56% of working personnel struggle with managing data. These inefficiencies are some of the issues Industrie 4.0 business models address.
Data-driven inventory optimization seeks to limit waste by accurately collecting data. This business model focuses on collecting factory inventory data and matching it with demand. Thus, factory owners get a complete assessment of what goods or materials are in warehouses. The collected data can also be used to predict future demand and assist in meeting it. It enables eliminating the hoarding of perishable goods and materials that lead to waste.
Material handling and transportation is another culprit that affects profitability. First, using inadequate material handling equipment (MHE) leads to product damage. Secondly, when just-in-time delivery is needed, late delivery leads to downtime. In factories, material handling procedures have been responsible for the majority of accidents that occur on the shop floor. These accidents are due to not understanding equipment capacity and poor maintenance culture. Once again, data is at the center of ensuring safety in factories.
Industrie 4.0 business models can optimize the workflow in factories. Data-driven plant performance optimization can be integrated into warehouses and factories. Here, an industrial cloud solution such as Corvina Cloud can serve as the data collection point. The collected data can be used to determine the factory's load capacity. With this knowledge, smarter material handling equipment can be customized to meet transportation requirements. Examples of such smart options are automated guided vehicle systems and tugger trains. These MHEs can also be equipped with sensors that collect data.
The data collected from material handling equipment can also be utilized in Industrie 4.0. The predictive maintenance business model focuses on using machine data to forestall total breakdown. With the correct material handling equipment and an interconnected ecosystem, maintenance procedures can be automated. SCADA systems are examples of Industrie 4.0 solutions that can be used to extensively monitor the performance of this equipment.
To reduce accidents across factory shop floors, customized material handling equipment can also be used. This equipment can be ultra-modern but expensive. Solutions like robots or traditional carts equipped with smart features are more affordable. In this case, MHEs can be equipped with speed sensors and mapping solutions. The sensors enable automating the speed of moving equipment and reduce the need for human assistants in shop floors.
The measured pace of the MHEs in relation to load weight ensures transportation stability. So, transporting goods across workstations is automated. This limits damage to transported products and supports just-in-time deliveries. Factory owners can take advantage of these benefits to eliminate inefficiency that results in downtime.
The purchase of manufacturing equipment generally accounts for much of the total overhead cost of a factory. Although manufacturing equipment tends to be durable, the total cost of ownership (TCO) is usually more than what most SMEs can handle. Entrepreneur listed the TCO associated with machinery as one of the issues hindering business growth.
Industrie 4.0 can also come to the rescue in these situations. An example of this is the growing Machine as a Service (MaaS) niche. Here, original equipment manufacturers (OEMs) can choose to sell machinery as a package under specific payment plans. One such purchasing plan is selling a machine at a reduced initial cost and remitting a percentage of sales to the OEM. This means with every product sold, a percentage of the money earned will be paid to the OEM.
Data Analysis is Key
The data a factory produces says a lot about the business and its operations. The eight Industrie 4.0 business models not only deliver business insights but provides practical assistance. Factory owners such as Aliexpress and Amazon have implemented the models with great success. Smaller factory owners can also leverage Industrie 4.0 models to solve challenges peculiar to medium-sized factories.
With predictive maintenance of factory equipment, machines and MHEs last longer. This reduces the amount spent on repairs and replacing damaged equipment. The data-driven inventory optimization ensures SMEs do not bite more than they can chew. Proper data analytics means inventory stays up-to-date and can be increased in real-time to meet demand.
When it comes to optimizing factory operations, data is truly king. Industrie 4.0 business model ensures factory owners can collect data from traditional processes and automate them. This will eliminate the important challenges relating to inventory, material handling, and downtime factories face.
Implementing these business models start with analyzing workflow that requires automating. Legacy machines and equipment must also be integrated with smart features for data collection. Finally, Factory owners must consider going down the managed-services route or break-fix solutions when choosing an Industrial cloud. Managed services mean using only what you need and scaling features at need while break-fix focuses on in-house management or calling the professionals when issues occur.