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Five Principles You Need To Know For Creating Better User Experience

The success of an app depends on the user’s experience and creating a good mobile user experience depends on good UI and performance of an app. To delight users of an app, the designer needs to take into consideration five major points while designing for the perfect execution of UX fundamentals.

    1. Be Unique, Charming and ConsiderateBe Unique: Know what makes your app different and amplify it. There are lots of mobile apps and if there’s nothing special about your app, why would anyone download it? So beforehand, plan an image of what you are going to create and what would be the uniqueness in your design that would attract users.untitled-infographic_block_1 Be charming: Mobile devices are intensely personal. They are our constant companions. Apps that are friendly, reliable and fun are always delightful to use, and people will become quite attached to the experience. So, the designer needs to keep in mind what should be put while creating a UI that will charm user of an app. Be considerate: App developers too often focus on what would be fun to develop and while developing an app, they put their own mental perception in an app or their personal business goals. These are good places to start, but you have to put yourself in your user’s shoes if you ever hope to create an engaging experience.
    2. User Experience Platform
      To begin to think from the perspective of our users, we need to consider three major mobile contexts: Bored, Busy and Lost.Bored: There are a lot of people using their smartphones on the couch at home. The impressive and delightful experiences would gear towards a longer usage session to overcome boredom. Still, there would be interruptions more often while using an app, so be sure your app can pick up where your user left off. Examples: Facebook, Twitter, Angry Birds, web browser.Busy: The ability to accomplish micro-tasks quickly and reliably with one hand in a hectic environment is critical. Remember that the user would have other tasks to accomplish and will have less time to concentrate, so huge targets and bold design are important. Examples: TripIt, email, calendar, banking.Lost: Users who are in transit or in familiar surroundings, but interested in something unknown, sketchy connectivity and battery life are big concerns. You should offer some level of offline support and be sparing with your use of geolocation and other battery hogs. Typical examples: Maps, Yelp, Foursquare.
    3. Use Clear and Simple Icons
      A picture is worth 1,000 words, and a visual interface icon is worth 10,000 lines of code. When designing a mobile app, create simple icons that articulate with the user and help users to achieve better experience. For example, you could use a checkmark to indicate that a task has been completed, a heart to show that something has been selected as a user’s favourite, or the familiar volume iconography to indicate when the sound has been turned on or off. Icons take up less space than the text and would be required to explain a function, giving you more room on screen.
    4. Minimalism

 

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As a designer, you need to keep in mind what would bring better user experience. The best way to increase better user experience is by reducing or removing unnecessary clutter, overbearing features and elements that come with drawbacks.
Rather than adding confusing elements that would cause an interaction mess, instead of that build an app that does one or two things extraordinarily well, with better options or features that are absolutely required to get the job done. This simplicity will help the user to focus on the purpose and effectiveness of your app, making it functional for users of all skill levels.

5.Screenshots
Clear and crisp screenshots would help you when your mobile apps are going up in App stores. With these screenshots user would get an idea about what app does. Yet, if an app performs badly, it will result in poor user experience. If it takes too long to load, crashes regularly, or the central server is down; you can’t fix those problems by fixing the aesthetic appeal of your offering. So, while designing and developing an app, designer and developer both need to take all points into consideration and eliminate elements which will degrade performance and result in the bad user experience.
The design should be easy to understand, which means it should be easier for your neighbour or grandmother to understand. For the most part, photos and digital images should be universally understood.The designer should consider and focus on elements which would reduce text. This will make sure that your app is usable for people of any language, you increase your reach exponentially—something that should make both your development team and potential users happy.

 

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Will AI Be the Future’s Definition of Sustainable Manufacturing?

Governments worldwide are implementing strict energy and emission policies to drive sustainability and efficiency in industries:

  • China’s Dual Control Policy (since 2016) enforces strict limits on energy intensity and usage to regulate industrial consumption.
  • The EU’s Fit for 55 Package mandates industries to adopt circular economy practices and cut emissions by at least 55% by 2030.
  • Japan’s Green Growth Strategy incentivizes manufacturers to implement energy-efficient technologies through targeted tax benefits.
  • India’s Perform, Achieve, and Trade (PAT) Scheme encourages energy-intensive industries to improve efficiency, rewarding those who exceed targets with tradable energy-saving certificates.

These policies reflect a global push toward sustainability, urging industries to innovate, reduce carbon footprints, and embrace energy efficiency.

What’s driving the world to impose these mandates in manufacturing?

This is because the manufacturing industry is at a crossroads. With environmental concerns mounting, the sector faces some stark realities. Annually, it generates 9.2 billion tonnes of industrial waste—enough to fill 3.7 million Olympic-sized swimming pools or cover the entire city of Manhattan in a 340-foot layer of waste. Manufacturing also consumes 54% of the world’s energy resources, roughly equal to the total energy usage of India, Japan, and Germany combined. And with the sector contributing around 25% of global greenhouse gas emissions, it outpaces emissions from all passenger vehicles worldwide.

These regulations are ambitious and necessary. But here’s the question: Can industries meet these demands without sacrificing profitability?

Yes, sustainability initiatives are not a recent phenomenon. They have traditionally been driven by the emergence of smart technologies like the Internet of Things (IoT), which laid the groundwork for more efficient and responsible manufacturing practices.

Today, most enterprises are turning to AI in manufacturing to further drive efficiencies, lower costs while staying compliant with regulations. Here’s how AI-driven manufacturing is enhancing energy efficiency, waste reduction, and sustainable supply chain practices across the manufacturing landscape.

How Does AI Help in Building a Sustainable Future for Manufacturing?

1. Energy Efficiency

Energy consumption is a major contributor to manufacturing emissions. AI-powered systems help optimize energy usage by analyzing production data, monitoring equipment performance, and identifying inefficiencies.

  • Siemens has implemented AI in its manufacturing facilities to optimize energy usage in real-time. By analyzing historical data and predicting energy demand, Siemens reduced energy consumption by 10% across its plants. 
  • In China, manufacturers are leveraging AI-driven energy management platforms to comply with the Dual Control Policy. These systems forecast energy consumption patterns and recommend adjustments to stay within mandated limits.

Impact: AI-driven energy management systems not only reduce costs but also ensure compliance with stringent energy caps, proving that sustainability and profitability can go hand in hand.

2. Waste Reduction

Manufacturing waste is a double-edged sword—it pollutes the environment and represents inefficiencies in production. AI helps manufacturers minimize waste by enhancing production accuracy and enabling circular practices like recycling and reuse.

  • Procter & Gamble (P&G) uses AI-powered vision systems to detect defects in manufacturing lines, reducing waste caused by faulty products. This not only ensures higher quality but also significantly reduces raw material usage.
  • The European Union‘s circular economy mandates have inspired manufacturers in the steel and cement industries to adopt AI-driven waste recovery systems. For example, AI algorithms are used to identify recyclable materials from production waste streams, enabling closed-loop systems. 

Impact: AI helps companies cut down on waste while complying with mandates like the EU’s Fit for 55 package, making sustainability an operational advantage.

3. Sustainable Supply Chains

Supply chains in manufacturing are vast and complex, often contributing significantly to carbon footprints. AI-powered analytics enable manufacturers to monitor and optimize supply chain operations, from sourcing raw materials to final delivery.

  • Unilever uses AI to track and reduce the carbon emissions of its suppliers. By analyzing data across the supply chain, the company ensures that partners comply with sustainability standards, reducing overall emissions.
  • In Japan, automotive manufacturers are leveraging AI for supply chain optimization. AI algorithms optimize delivery routes and load capacities, cutting fuel usage and emissions while benefiting from tax incentives under Japan’s Green Growth Strategy.

Impact: By making supply chains more efficient, AI not only reduces emissions but also builds resilience, helping manufacturers adapt to global disruptions while staying sustainable.

4. Predictive Maintenance

Industrial machinery is a significant source of emissions and waste when it operates inefficiently or breaks down. AI-driven predictive maintenance ensures that equipment is operating at peak performance, reducing energy consumption and downtime.

  • General Electric (GE) uses AI-powered sensors to monitor the health of manufacturing equipment. These systems predict failures before they happen, allowing timely maintenance and reducing energy waste.
  • AI-enabled predictive tools are also being adopted under India’s PAT scheme, where energy-intensive industries leverage real-time equipment monitoring to enhance efficiency. (Source)

Impact: Predictive maintenance not only extends the lifespan of machinery but also ensures that energy-intensive equipment operates within sustainable parameters.

The Road Ahead

AI is no longer just a tool—it’s a critical partner in achieving sustainability. By addressing challenges in energy usage, waste management, and supply chain optimization, AI helps manufacturers not just comply with global mandates but thrive in a world increasingly focused on sustainability.

As countries continue to tighten regulations and push for decarbonization, manufacturers that embrace AI stand to gain a competitive edge while contributing to a cleaner, greener future.

Mantra Labs helps manufacturers achieve sustainable outcomes—driving efficiencies across the shop floor to operational excellence, lowering costs, and enabling them to hit ESG targets. By integrating AI-driven solutions, manufacturers can turn sustainability challenges into opportunities for innovation and growth, building a more resilient and responsible industry for the future.

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