Article | July 27, 2021
Filmmaking is manufacturing. To date, no one has made the direct correlation between the two. As many entertainment professionals know, the budget gap between indie productions and big studio blockbusters continues to grow. The day of mid-budget, independent (indie) movies is disappearing as fast as the middle class in the American economy. According to newbiefilmschool, the average budget is barely at $2 million for these pictures and producers have been forced to adapt by discovering creative ways to decrease costs, while maintaining a high production values for a sophisticated audience with high expectations.
Though there are many ways to cut costs, any business professional will agree to go with the options that bring down the budget the most. Just as dog is man’s best friend, here are three reasons why manufacturers have become the same for a filmmaker by saving money and time for every type of production.
Film equipment manufacturers
No long may a film lack quality in picture, sound, and bad acting. Once acceptable, these older movies were produced with the technology and film equipment constraints and from limited funding. Film equipment manufacturers from cameras, sound equipment, and computers cost less to achieve high production values. Film equipment companies face increasing competition, which has driven down the purchase price. Better equipment with significant technology improvements has reframed the indie film industry with high-level sound and image capture quality.
The transition of cameras from film to digital was a notable shift for manufacturers. Many industry-insiders believe that digital is free, and film is expensive, but there is more the manufacturing construct. Digital cameras, when compared to film cameras in the same market price bracket, are much more expensive than analog counterparts. It is true that film costs money and is single-use. Digital memory cards are relatively expensive and can be reused. Film also needs to be developed and there is a cost associated with that production cost. There are other ways in which digital modalities save filmmakers.
Across all industries, efficiency always wins. Innovative manufacturers have developed machines to make numerous jobs easier for everyone. Machines have been assisting filmmakers since the invention of the camera. AI (artificial intelligence) is poised to change film even more and continues to augment human creativity. Storytellers work with computers during every process of creating a motion picture which has sped up the time it takes to complete each-step in film making.
Automating pre-production processes, such as creating a budget and writing a script, is analogous to an ERP (enterprise resource planning) software for a traditional manufacturing operation. The Movie Magic budgeting software by Entertainment Partners has made creating a budget more efficient and accurate. Screenwriter programs vary from the downloadable Final Draft, and the purely cloud based, Celtx, are the reasons automated scriptwriting is the norm. These programs also automatically format writing to industry standards, facilitating the creative process.
Automation in post-production is equally advanced through editing software for video, sound, effects, and colors all the way to distribution and promotional content. Editing footage from digital rather than film saves time and money. Industry favorites include Adobe Premiere Pro and Apple’s exclusive Final Cut Pro and are used on almost all well-known movies and TV shows.
The impacts of COVID-19 on entertainment manufacturers
Without question, the pandemic has affected every industry by creating an unanticipated production standstill. Entertainment manufacturers have sacrificed countless productions, lost billions of dollars, and major talent agencies have furloughed hundreds of employees. This negative impact is not just difficult for indie filmmakers, big studios are suffering just as much with production delays and cancellations still happening as this article goes to press.
Any way back to the set is better than no set at all. A new necessity for productions to safely reopen includes epidemiologists and other public health specialists; they provide detailed strategies dealing with large crews who work in cramped spaces, makeup artists who get face-to-face with actors who kiss, hug, and fight on set. These COVID-19 consultants rely on the manufacturing industry for PPE supplies and carry out regular PCR tests. Face coverings and hand sanitizing stations have also become the norm, just like most other manufacturing operations.
Article | January 3, 2022
Production planning and control are critical components of any manufacturing organization. It helps organizations with the regular and timely delivery of their goods. Furthermore, it allows manufacturing businesses to increase their plant’s efficiency and reduce production costs.
Numerous software and tools for production scheduling and planning are available on the market, including Visual Planning, MaxScheduler, and MRPeasy, which assist manufacturing organizations in planning, scheduling, and controlling their production.
According to KBV Research, the manufacturing operations management software market is anticipated to reach $14.6 billion by 2025 globally, expanding at a market growth of 10.2 percent CAGR during the forecast period.
So, what exactly is production planning and control?
Production planning is an administrative process within a manufacturing business. It ensures that sufficient raw materials, personnel, and other necessary items are procured and prepared to produce finished products according to the specified schedule.
Scheduling, dispatch, inspection, quality control, inventory management, supply chain management, and equipment management require production planning. Production control makes sure that the production team meets the required production targets, maximizes resource utilization, manages quality, and saves money.
“Manufacturing is more than just putting parts together. It’s coming up with ideas, testing principles and perfecting the engineering, as well as final assembly.”
– James Dyson
In oversize factories, production planning and control are frequently managed by a production planning department, which comprises production controllers and a production control manager. More significant operations are commonly monitored and controlled from a central location, such as a control room, operations room, or operations control center.
Why Should You Consider Production Planning?
An efficient production process that meets the needs of both customers and the organization can only be achieved through careful planning in the early stages of production. In addition, it streamlines both customer-dependent and customer-independent processes, such as on-time delivery and production cycle time.
A well-designed production plan minimizes lead time, the period between placing an order and its completion and delivery. The definition of lead time varies slightly according to the company and the type of production planning required. For example, in supply chain management, lead time refers to the time required for parts to be shipped from a supplier.
Steps in Production Planning and Control
The first stage of production planning determines the path that raw materials will take from their source to the finished product. You will use this section to determine the equipment, resources, materials, and sequencing used.
It is necessary to determine when operations will occur during the second stage of production planning. In this case, the objectives may be to increase throughput, reduce lead time, or increase profits, among other things. Numerous strategies can be employed to create the most efficient schedule.
The third and final production control stage begins when the manufacturing process is initiated. When the scheduling plan is implemented, materials and work orders are released, and work is flowing down the production line, the production line is considered to be running smoothly.
The fourth stage of manufacturing control ascertains whether the process has any bottlenecks or inefficiencies. You can use this stage to compare the predicted run hours and quantities with the actual values reported to see if any improvements can be made to the processes.
Production Planning Example
Though production planning is classified into several categories, including flow, mass production, process, job, and batch, we will look at a batch production planning example here.
Manufacturing products in batches is known as "batch production planning." This method allows for close monitoring at each stage of the process, and quick correction since an error discovered in one batch can be corrected in the next batch. However, batch manufacturing can lead to bottlenecks or delays if some equipment can handle more than others, so it's critical to consider capacity at every stage.
Consider the following example of batch production planning:
Jackson's Baked Goods is in the process of developing a production plan for their new cinnamon bread. To begin with, the head baker determines the batch production time required by the recipe.
He then adjusts the bakery's weekly ingredient orders to include the necessary supplies and schedules the weekly cinnamon bread bake during staff downtime.
Finally, he creates a list of standards for the bakery staff to check at each production stage, allowing them to quickly identify any substandard materials or other batch errors without wasting processing time on subpar cinnamon bread.
Running a smooth and problem-free manufacturing operation relies heavily on a precise production planner. Many large manufacturing companies already have a strong focus on streamlining their processes and making the most of every manufacturing operation, but small manufacturing companies still have work to do in this area. As a result, plan, schedule, and control a production that will enable you to run your business in order to meet its objectives.
What is the difference between planning and scheduling in production?
Production planning and scheduling are remarkably similar. But, it is critical to note that planning determines what operations need to be done and scheduling determines when and who will do the operations.
What is a production plan?
A product or service's production planning is the process of creating a guide for the design and manufacture of a given product or service. Production planning aims to help organizations make their manufacturing processes as productive as possible.
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.
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Article | October 8, 2021
The trends in the manufacturing industry for 2022 are expanding and altering the industry's conventional face. The future of manufacturing is going to merge with digitalization and technological applications. As a result, all operation methods, products, and manufacturing outcomes will be modernized with new technology applications.
To brighten the future of manufacturing, manufacturing companies must examine new trends in the industry before developing their manufacturing plans for 2022. Technological advancements are the next game-changer in the manufacturing business.
Adeaca's Vice President of Market Innovation and Project Business Evangelist had recently quoted in an interview with Media7 as,
“As technology takes over and enhances many of the processes we used to handle with manual labor, we are freed up to use our minds creatively, which leads to bigger and better leaps in innovation and productivity.” – Matt Mong, VP Market Innovation and Project Business Evangelist at Adeaca
The new trends in manufacturing are leveling up every part and element of the industry. In this article, we'll look at a new trend for each industry aspect that's assisting manufacturers in speeding up the production process, increasing ROI, and propelling their manufacturing business to new heights.
Additionally, it will assist you in addressing current industry challenges such as forecasting product demand, addressing skilled manpower shortages, and increasing manufacturing plant efficiency.
Five Manufacturing Industry Trends to Watch in 2022
Emerging trends in manufacturing provide a chance to review your production strategy for products and processes. Check out below the upcoming trends in manufacturing that are getting attention in the industry.
Customer Engagement and Purchase Experience
Creating an exceptional digital customer experience is a new trend in manufacturing. According to industry experts, mapping the customer journey and their interactions with your products is the first step towards establishing a positive connection with your potential consumers.
A few of the most popular strategies to improve the consumer purchasing experience and engagement are as follows:
Build a knowledge base for your products on your business website
Create a comprehensive FAQs page that addresses all of the buyer's possible queries
Create a chatbot to provide immediate help to the buyer with further inquiries
Create a brand story and a comprehensive description of your manufacturing business
If possible, provide product statistics and success stories, and content about consumer satisfaction with your product
Create a product functionality video or explanatory picture material to familiarize the potential customer with your product
These are some of the trends that engage your prospective buyers and increase their purchasing experience through a range of product-related information and educate them about you and your products.
Smart Technology-enabled Products
Smart is the new norm in every industry. The old operations and goods that were once a part of everyone's life have now been replaced by technology. Manufacturing is no exception to this alteration. Due to the increasing demand for smart products among customers, every company is now looking forward to inventing and manufacturing smart products.
Explore and understand how you may incorporate cutting-edge technology (Artificial Intelligence, Machine Learning, Edge Computing, and Digital Twins, and more) into your products to help them stay updated with manufacturing trends.
Virtual and Augmented Reality in Manufacturing (Industry 4.0)
Transforming traditional manufacturing systems and processes into smart, tech-savvy ones is a new trend in manufacturing. The future of manufacturing is expected to witness this digitization in 2022 and beyond. Therefore, you must convert your conventional manufacturing plants into smart ones, i.e., as per the concept of Industry 4.0 – the fourth industrial revolution.
Discover how prominent companies are implementing Industry 4.0
The following are some popular transformations that many popular manufacturing factories are adopting to become part of the industry revolution.
To achieve a zero-carbon footprint, manufacturers may use analytics systems to determine the amount of trash they create and develop ways to eliminate it. (Implemented by Whirlpool)
Utilize an analytics platform to decipher usage data for energy, water, and other utilities. (Implemented by Whirlpool)
Utilize technology such as Siemens' Mindsphere, which enables online analysis of several aspects of a production plant and helps manufacturers create digital models using real-time data. (Implemented by Siemens)
Utilize a combination of IoT and cloud-based technologies to avoid downtime and gather analytics data. (Implemented by Hirotec – a Japan based manufacturing company)
Machine learning technology can be used to foretell and avoid system failures in your manufacturing plant. (Implemented by Hirotec – a Japan based manufacturing company)
Utilize robotics and to accelerate manufacturing across many verticals. (Implemented by Ford)
Utilize 3D printing to improve the precision of product design and to avert product defects during the early production stage. (Implemented by Aerospace: Airbus) These are some examples that other well-known manufacturing companies in the market, such as Hewlett-Packard, Ford, Whirlpool, and Siemens are currently using. So, consult an expert and determine how to leverage emerging technology to turn your production plant into a smart manufacturing unit.
Internet of Things (IoT) to Boost Revenue
Manufacturing companies have begun to leverage the Internet of Things to establish connectivity between machines and operational procedures throughout manufacturing. This linkage between machine and operation significantly decreases the human supervision required for each step and completely automates them.
Manufacturers intend to incorporate these IoT trends in manufacturing into both their products and operational processes. IoT further enables manufacturers to operate and monitor their work remotely. As a result, they can concentrate on developing new strategies and preparing for future ventures.
Shifting Focus from B2B to B2C Model
Several manufacturers skip intermediaries and connect directly with their consumers to sell efficiently to their target consumer group. This purposeful approach has multiple benefits, which are outlined below.
Manufacturers may skip the lengthy retail sales cycle and achieve a shorter time to market
The absence of a third party between the manufacturer and the customer reduces the risk of brand misinterpretation or dilution
Direct interaction with customers enables manufacturers to obtain more accurate consumer data, product feedback, and requirements for new product development
Manufacturers can control the price of their products due to the absence of a third party between them and the target consumer group
These benefits of the B2C model attract manufacturers and encourage them to develop added production techniques with these benefits in mind.
Technology, innovation, and digitization are the future of manufacturing. The IoT trends in manufacturing are essential for industrial production and will allow the manufacturing industry to obtain a new competitive edge. Hence, manufacturers must keep in mind this industry revolution (industry 4.0 and 5.0) while developing strategies for their manufacturing operations in 2022.
What are the benefits of adopting the Internet of Things in manufacturing?
IoT devices can monitor industrial operations, manufacturing cycles, and other warehouse data management processes automatically. This benefit decreases the amount of time spent monitoring individual operations and increases production speed.
What role will smart manufacturing play in the future?
According to a grand view research analysis, the smart manufacturing market was worth USD 236.12 billion in 2020 and is expected to extend at a 12.4 percent compound annual growth rate to reach USD 589.98 billion by 2028.
What are the critical components of the smart factory of the future?
Robotics, the Internet of Things, big data, and cloud-based administration will be critical components of the future smart factory.