Article | December 7, 2021
Machine learning in manufacturing is becoming more widespread, with businesses like GE, Siemens, Intel, Bosch, NVIDIA, and Microsoft all investing heavily in machine learning-based ways to enhance manufacturing.
Machine learning is predicted to expand from $1 billion in 2016 to USD 9 billion by 2022at a compound annual growth rate (CAGR) of 44% throughout the forecast period, according to Markets & Markets.
The technology is being utilized to cut labor costs, achieve better transition times, and increase manufacturing speed.
“I advocate business leaders get to know more about what AI can do and then leverage AI in proofs of concept.”
– Michael Walton, Director and Industry Executive, Microsoft speaking with Media 7
Machine learning can help enhance manufacturing processes at the industrial level. This can be achieved by assessing current manufacturing models and identifying flaws and pain factors. Businesses can rapidly address any difficulties to keep the manufacturing pipeline running smoothly.
Let us explore how machine learning is transforming manufacturing operations.
How Machine Learning Is Transforming Manufacturing Operations
“The greatest benefit of machine learning may ultimately be not what the machines learn but what we learn by teaching them.”
- Pedro Domingos
Machine learning in manufacturing is revolutionizing manufacturing operations and making them more advanced and result-oriented, so let's have a look at how this is unfolding.
Allows for Predictive Maintenance
Machine learning provides predictive maintenance by forecasting equipment breakdowns and eliminating wasteful downtime. Manufacturers spend far too much time correcting problems instead of planning upkeep. In addition to enhancing asset dependability and product quality, machine learning systems can forecast equipment breakdown with 92% accuracy. Machine learning and predictive analytics increased overall equipment efficiency from 65% to 85%.
Increases Product Inspection and Quality Control
Machine learning is also utilized for product inspection. Automated inspection and supervision using ML-based computer vision algorithms can discriminate between excellent and bad products. These algorithms simply need excellent samples to train; therefore a fault library is not required. However, an algorithm that compares samples to the most common errors can be built. Machine learning reduces visual quality control costs in manufacturing. Forbe's says AI-powered quality testing can boost detection rates by up to 80%.
Logistics-related Tasks Are Automated
To run a production line, industrial companies need considerable logistics skills. The use of machine learning-based solutions can improve logistics efficiency and save expenses. Manual, time-consuming operations like logistics and production-related documentation cost the average US business $171,340 annually. It saves thousands of manual working hours every year to automate these everyday procedures. Using Deep Mind AI, Google was able to lower its data center cooling bill by 40%.
Creates More Business Opportunities
Machine learning is frequently used in the production process. Substantial data analysis is required to create new items or improve existing products. Collection and analysis of huge amounts of product data can help find hidden defects and new business opportunities. This can help improve existing product designs and provide new revenue streams for the company. With machine learning, companies can reduce product development risks by making smarter decisions with better insights.
Protects Company’s Digital Assets
On-premise and cloud-based machine learning systems require networks, data, and technological platforms to function. Machine learning can help secure these systems and data by restricting access to vital digital platforms and information. Humans’ access sensitive data, choose applications, and connect to it using machine learning. This can help secure digital assets by immediately recognizing irregularities and taking appropriate action.
Harley Davidson's Sales Climbed by 40% Using Albert – The ML & AI-Powered Robot
Today, traditional marketing is harder to break through. It's easy to see why Albert (an AI-powered robot) would be a good fit for Harley Davidson NYC. Thanks to machine learning and artificial intelligence, robots are producing news stories, working in hotels, controlling traffic, and even running McDonald's.
Albert works well with social media and email marketing. It analyzed which customers are more likely to convert and modifies the personal creative copies on its own for the next process.
Harley-Davidson is the only company to employ Albert in its business. The company evaluated customer data to find prior consumers who made purchases and spent more time browsing the website than normal. Albert used this data to categorize customers and scale up test campaigns.
Using Albert, Harley-Davidson's sales climbed by 40% and leads increased 2,930%, with half coming from high-converting ‘lookalikes' detected by AI and machine learning.
The groundbreaking benefits of machine learning are the pillars of machine learning applications in manufacturing. Machine learning in manufacturing helps enhance productivity without compromising quality. According to Forbes, Amazon has automated warehouse logistics picking and packing using a machine learning system. With Kiva's help, Amazon's typical ‘click to ship' time dropped from 60-75 minutes to 15 minutes. So, industry leaders are seeing fantastic outcomes, and machine learning in manufacturing is the future.
How is machine learning used in manufacturing?
Machine learning is used in manufacturing to improve product quality and uncover new efficiencies. It unquestionably aids in the identification and removal of bottlenecks in the manufacturing process.
Which two forms of machine learning are there?
Machine learning is divided into two forms: supervised and unsupervised. In supervised machine learning, a machine learning algorithm is trained using data that has been labeled. Unsupervised ML has the advantage of working with unlabeled data.
What is a machine learning model?
A machine learning model is a file that can recognize patterns. In order to learn from a set of data, you must first train a model using an algorithm.
"name": "How is machine learning used in manufacturing?",
"text": "Machine learning is used in manufacturing to improve product quality and uncover new efficiencies. It unquestionably aids in the identification and removal of bottlenecks in the manufacturing process."
"name": "Which two forms of machine learning are there?",
"text": "Machine learning is divided into two forms: supervised and unsupervised. In supervised machine learning, a machine learning algorithm is trained using data that has been labeled. Unsupervised ML has the advantage of working with unlabeled data."
"name": "What is a machine learning model?",
"text": "A machine learning model is a file that can recognize patterns. In order to learn from a set of data, you must first train a model using an algorithm."
Article | December 21, 2021
When it comes to developing a budget for the following financial year of your manufacturing business, many operations managers start with direct labor and material expenditures. But, what about manufacturing overhead costs?
Manufacturing overhead is any expense not directly tied to a factory's production. Therefore, the indirect costs in manufacturing overhead can also be called factory overhead or production overhead.
Outsourcing and globalization of manufacturing allows companies to reduce costs, benefits consumers with lower-cost goods and services, and causes economic expansion that reduces unemployment and increases productivity and job creation.
– Larry Elder
So, this article focuses on some highly effective overhead cost reduction methods that would help you build a healthy budget for the following year.
Manufacturing Overhead Costs: What Is Included?
Everything or everyone within the factory that isn't actively producing items should be considered overhead.
The following are some of the variables that are considered overhead costs:
Depreciation of equipment and productionfacilities
Taxes, insurance, and utilities
Supervisors, maintenance, quality control, and other on-site personnel who aren't producing signs
Indirect supply from light bulbs to toilet paper is also included in the overhead cost.
Manufacturing Overhead Costs: What Is Excluded?
Everything or everyone within or outside the factory that is actively producing items should be excluded from the overhead costs.
Factory overhead does not include the following:
Employee costs for those making the goods daily
External administrative overhead, such as a satellite office or human resources
Costs associated with C-suite employees
Expenses associated with sales and marketing - include pay, travel, and advertising
How to Calculate Overhead Costs in Manufacturing
To know the manufacturing overhead requires calculating the manufacturing overhead rate. The formula to calculate the manufacturing overhead rate i.e. MOR is basic yet vital.
To begin, determine your overall manufacturing overhead expenses. Then, add up all the monthly indirect expenditures that keep manufacturing running smoothly.
Then you can calculate the Manufacturing Overhead Rate (MOR). This statistic shows you your monthly overhead costs as a percentage.
To find this value, divide Total Manufacturing Overhead Cost (TMOC) by Total Monthly Sales (TMS) and multiply it by 100. The final formula will be:
Assume your manufacturing overhead expensesare $50,000 and your monthly sales are $300,000. You get.167 when you divide $50,000 by $300,000. Then increase that by 100 to get your monthly overhead rate of 16.7%.
This means your monthly overhead expenditures will be 16.7% of your monthly income. Being able to forecast and develop better solutions to decrease production overhead.
Five Ways to Reduce Manufacturing Overhead Costs
A variety of strategies may be used by manufacturing organizations to reduce their overhead costs. Here is a summary of some of the most important methods for reducing your manufacturing overhead costs.
Value Stream Mapping – A Production Plant Process Layout
A value stream map depicts the entire manufacturing process of your plant. Everything from raw material purchase through client delivery is detailed here. The value stream map provides you with a complete picture of the profit-making process. This overhead cost-cuttingmethod is listed first for a reason because every effort to reduce manufacturing overhead costsstarts with a value stream map.
Lean manufacturingis also one of the techniques of eliminating unnecessary time, staff, and work that is not necessary for profit and has gained undue favor in the manufacturing process. You must first create a value stream map of the whole manufacturing process for this technique to work. Once the lean manufacturing precept is established, the following strategies for decreasingmanufacturing overhead expenses can be examined.
Do Not Forget Your Back Office Management
Before focusing on factory floor cost reduction techniques, remember that your back offices, where payment processing and customer contacts occur, may also be simplified and increase profitability. Fortunately, automation can achieve this profitability at a cheap cost.
Manufacturers increasingly use robotic process automation (RPA) to sell directly to customers rather than rely on complex supply networks. This automation eliminates costly human mistakes in data input and payment processing by automatically filling forms with consumer data. Moreover, the time saved from manual data input (and rectifying inevitable human errors) equates to decreased labor expenses and downtime.
Automating Your Manufacturing Plant
For a long time, manufacturers saw factory automation as a game-changer. As a result, several plant owners make radical changes in their operations using cutting-edge technologydespite knowing it realistically. Over-investing in technologies unfamiliar to present industrial personnel might be deemed a technology blunder. Investing in new technology that doesn't generate value or is too hard for current staff to use might be a mistake.
It's usually best to start small when implementing newtechnology in manufacturing. Using collaborative robots in production is one way to get started with automation. They are inexpensive, need little software and hardware, and may help employees with mundane, repeated chores that gobble up bandwidth. It is a low-cost entry point into automation that saves labor expenses and opens the door for further automation investments when opportunities are available.
Reuse Other Factory Equipment and Supplies
Check with other factories to see if they have any unused equipment or supplies that may be "redeployed" to your manufacturing plant. Redeployment would save you time and money by eliminating the need to look for and install new equipment while lowering your overhead costs.
Outsourcing a fully equipped factory, equipment, or even staff can also assist in lowering overhead costssince you will only pay for what you utilize. As such, it is a viable method to incorporate into your production process.
Employ an In-house Maintenance Expert
An in-house repair technician can service your equipment for routine inspections, preventive maintenance, and minor repairs. This hiring decision might save money on unforeseen repair expenses or work fees for an outside repair provider. Having someone on-site who can do emergency repairs may save you money if your equipment breaks after business hours.
Manufacturing overhead costis an essential aspect of every manufacturing company's budget to consider. Smart manufacturingis intended to be productive, efficient, and cost-effective while effectively managing production expenditures. Calculating the manufacturing overheadcan provide you with a better understanding of your company's costs and how to minimize them. Depending on the conditions or geographical needs, each manufacturing plant's overhead expensesmay vary. As a result, identify your production overhead costsand concentrate on reducing and improving them.
What are manufacturing overheads?
Manufacturing overhead cost is a sum of all indirect expenses incurred during production. Manufacturing overhead expenses usually include depreciation of equipment, employee salaries, and power utilized to run the equipment.
What is a decent overhead percentage?
When a business is functioning successfully, an overhead ratio of less than 35 % is considered favorable.
How can I calculate the cost of manufacturing per unit?
The overall manufacturing cost per unit is determined by dividing the total production expenses by the total number of units produced for a particular time.
Article | May 25, 2021
Additive manufacturing offers the potential to accelerate the pace of electronics manufacturing by creating a number of unique opportunities, such as the ability to combine multiple materials in single print jobs. The technology is also much more accessible than it previously was. Plus, it enables faster prototyping, which could speed the time to market and prevent costly mishaps that disrupt the production process. Here’s a look at some of the many benefits additive manufacturing brings to the electronics sector.
One Giant Leap
Adoption rates for electronics made with additive manufacturing will continue to climb as people realize its versatility. Thanks to a new project associated with students at Embry-Riddle Aeronautical University, we could see materials made with additive manufacturing are as well-suited for use in space as on Earth.
Article | April 6, 2021
As the pandemic upended plans for marketing and sales in 2020, it forced marketers in the manufacturing industry to adopt the tactics of the remote world. Many of them are still wondering how they can focus on driving business growth in 2021. Intent data has undoubtedly added some spice to the season of online marketing.
Research conducted by B2BecNews on 110 businesses found that 59.5% of business buyers research two to three websites before buying while 29.7% research up to seven websites.
The “How” of Intent Data
Intent data allows businesses to channel their expenditure to the leads that matter the most. It boosts sales and encourages marketers to be smarter by doing more in less time.
Moreover, b2b buyers now tend to look for an immersive digital experience and are likely to conduct more and more searches before engaging with a brand. Such digital activity will tell you what a visitor’s intentions are called the intent data.
To drive your business, here are some tried-and-true and unexpectedly productive ways to scale up your marketing and sales game using intent data.
Improve your Sales Pitches/Pipelines
When you are expanding or redefining your business because you want to target a new market or audience, third-party intent data is a decent place to start. Through intent data, your sales team can build a year’s pipeline by reaching target audiences.
To get the value of your sales, you can use intent data categorizing with a professional group, seniority, functional area, business size, and more for targeted prospects. And if your data provides contact information, your sales team will have an even deeper understanding of the dynamics of prospects’ buying activities.
Moreover, learning about the fact if a CEO or a random visitor visits your website creates a difference between a quality lead and a generic one. There are times when organizations don’t vigorously look for a product. But with the right content force, you can direct them towards a purchase decision. This way, you can get a chance to pitch and improve sales.
So, how can content pitch sales?
The next point explains the importance of nurturing content on your website.
Nurture with Personalized Content
Once you target new prospects, you can nurture them with excellent and informational marketing content. These can be in various forms like articles, blogs, advertisements, social media, infographics, and more.
Personalization results better in the sea of marketing (digitally or manually). Since the pandemic has pushed the digital world extensively, personalization is on a hike. Companies that personalize their marketing strategies to communicate are improved by 86% in customer relations, have higher conversation rates, and observed improvement in businesses.
To personalize your content, you have to look at intent data and search for the prospect’s interests. After your research, you can create content for them. Paying attention to contextual information will improve the prospect’s experience, causing them to turn into your client.
After you create personalized content, what will happen next? Find out ahead.
Generate High-Quality Leads
Intent data tells you how far each prospect has progressed. A combination of intent and context data helps with lead scoring, which shows you the quality of leads.
A visit to your website by an intern is somewhat different from a CEO’s visit.
Consuming content on general industry information differs in value from product-specific content that provides information on websites.
When a visitor compares prices, it intends to buy, opposite to a visitor who bookmarks pages.
Besides, intent data for manufacturers also tells:
Channels to target your prospects actively.
Content to encourage
Offers to serve
The timing of each lead nurturing action
Improve Account-Based Marketing Campaigns
Account-based marketing and intent data go hand-in-hand. So, it would be best if you worked through every possible path to collect more information about your prospects. This way, it will help you take a focused approach. Once you identify the interested prospects, you can focus your time and energy on those accounts and expand your reach.
Intent data helps you to find more in-market customers. They can score leads with better precision and re-shape your marketing campaigns by showing up with the right message at the right time.
Include Marketing Automation Operations
Implementing marketing automation technologies with intent data will save your team's time. As they usually spent analyzing data entry by automatically setting alerts when buyers intend to show their interest.
Why is Intent Data for Manufacturing Becoming Crucial for Future?
With marketers, or say, manufacturing marketers, it's always vital to drive revenue for business and get ahead with trending marketing paths. For this, knowing intent of prospects is a must to gain success.
Knowing a prospector’s behavior can help your marketing team target a specific profile and create personalized content on demand to increase their purchase decision. After all the information is collected, prospects become more knowledgeable and informed of the decision they make. More information attracts more potential buyers when they are informed conveniently at the right time and manner. In this entire process, you gain an increased ROI.
These aspects are incomplete without intent data for manufacturers, which targets numerous data and creates an easy baseline so that marketers can learn precisely about potential prospects’ behaviors. Intent data can be used for the future through a particular pattern. Generic marketing campaigns delivered to a random audience will simply shut down your business. Because now, the users expect to see content that’s valuable to them.
Therefore, intent data for manufacturers is the key to providing better answers and solutions and allowing better marketing budgets. Both of these lead to more conversions which results in more revenue.
Frequently Asked Questions
How is intent data collected?
The collection of intent data is not new to marketers. It has gained prominence only after the pandemic. The data is gathered through the website. Its analysis is done by tracking visitors to the website, clicks, chatbots, duration of stay, and information search.
How can manufacturers leverage intent data?
The steps to leverage are:
1. identify the prospect and what it wants to search or trying to search. It could be keywords, trending words or phrases, and more.
2. Create quality yet informational content following the prospects’ interest.
3. Now, it’s time to promote content with the right on different channels to attract prospects.
What are the intent data tools for manufacturers?
Some good intent data tools manufacturers can use are:
What is buyer intent data for manufacturers?
Through buyer intent data, your sales team easily reaches out and gets engaged with the right prospect at the right time. Manufacturing marketers use it to plan can create effective campaigns to target potential ones and convince them to buy.
"name": "HOW IS INTENT DATA COLLECTED?",
"text": "The collection of intent data is not new to marketers. It has gained prominence only after the pandemic. The data is gathered through the website. Its analysis is done by tracking visitors to the website, clicks, chatbots, duration of stay, and information search."
"name": "HOW CAN MANUFACTURERS LEVERAGE INTENT DATA?",
"text": "The steps to leverage are:
1. identify the prospect and what it wants to search or trying to search. It could be keywords, trending words or phrases, and more.
2. Create quality yet informational content following the prospects’ interest.
3. Now, it’s time to promote content with the right on different channels to attract prospects."
"name": "WHAT ARE THE INTENT DATA TOOLS FOR MANUFACTURERS?",
"text": "Some good intent data tools manufacturers can use are:
"name": "WHAT IS BUYER INTENT DATA FOR MANUFACTURERS?",
"text": "Through buyer intent data, your sales team easily reaches out and gets engaged with the right prospect at the right time. Manufacturing marketers use it to plan can create effective campaigns to target potential ones and convince them to buy."