Manufacturing

Improving Infrastructure, Assets & Efficiency

Top Manufacturing Data Challenges

  • Enabling greater selling, production and service agility with existing IT resources
  • Getting more value out of machine data and enabling greater manufacturing intelligence
  • Improving compliance reporting, quality management systems and reducing the time spent preparing for audits
  • Better supply chain visibility and collaboration to improve performance and drive down costs

Sound Familiar?

  • “How do we enable greater production with existing IT resources?”
  • “We understand the benefits brought by technology, but how do we pay for it and who will implement the improvements?”
  • “We have to improve supply chain visibility and collaboration to improve performance and drive down costs.”

Automation, the Industrial Internet of Things (IIoT), robotics, analytics cloud computing and more. Technology is advancing at warp speed and most manufacturers struggle to keep up let alone stay on the leading edge. By the time many IT departments have gone through the process of researching, getting approval, purchasing and installing new technology, a faster and more agile solution may emerge.

Legacy and homegrown systems are still relied on by the majority of manufacturing centres today, mainly because of they meet highly specific information needs.

The challenge is how to integrate legacy and homegrown systems with the latest applications and platforms, while still improving production quality and efficiency. Improving everything from quoting accuracy, order cycle times, product quality to perfect order performance is going to be one of the most challenging aspects of any manufacturing CIO’s job moving forward.

Real-time monitoring of each machine on the shop floor has become more commonplace. Pilot programs using the Internet of Things (IoT)-based sensors are running in hundreds of manufacturing plants right now.

All of these efforts centre around how to get more value out of machine data and accurately predict when predictive maintenance is required. Machine data and manufacturing intelligence is a challenge for many CIOs to implement, however. The potential to predict production efficiency and improve customer responsiveness is going to make this area one of the most important focuses in the future.

The team at DSCallards give businesses expert advice on the necessary improvements to be made to their data analytics infrastructure. With improved infrastructure, your business will benefit from greater security and improved company efficiency.

Manufacturing

Frequently Asked Questions

How is data analytics used in manufacturing?

Data analytics is used in a number of different ways in the manufacturing sector, most commonly to boost productivity and enhance performance, ensure product quality is maintained, optimise decision-making and lower overall costs. As a result, real-time data analytics is transforming the manufacturing industry by reducing human error and allowing for faster, more informed decision-making.

Data analytics can also help manufacturing businesses to:

  • Reduce capital expenditures
  • Increase profitability by better understanding consumer behaviour
  • Improve the accuracy of cash flow forecasting
  • Recognise profitability opportunities at both customer and product levels
  • Create a culture where decisions are informed using data
  • Recognise market share and help businesses gain a competitive edge
  • Improve distribution and logistics throughout the supply chain

To find out more about how data analytics can be utilised in your manufacturing business, contact DSCallards today. We’d be happy to help.

What are big data analytics in the manufacturing industry?

Analytics and transformation play an important role in pinpointing problem areas in the manufacturing industry. By highlighting certain areas that require improvement, data analytics allows employees to transform operations with more informed, timely and cost-effective actions and data-driven decisions that maximise growth and efficiency.

To find out more about how data analytics can be utilised in the manufacturing sector, contact the team at DSCallards today.

How can manufacturers benefit from data analytics?

Using data analytics, employees working in the manufacturing sector can swiftly collect and analyse machine data, which can reveal insights that aid in performance improvement. With comprehensive data collections across a business, decision-makers can also easily identify individual asset performance, underperforming shifts and recurring maintenance issues that require attention. Perhaps most important, data analytics aids in reducing unplanned machinery downtime and production bottlenecks, which can increase the effectiveness and productivity of the manufacturing floor.

To find out more about how data analytics can boost productivity, efficiency and profitability in your manufacturing business, contact the team at DSCallards today. We’ve been assisting manufacturing businesses for more than two decades and would be delighted to speak with you.

How do you analyse manufacturing data?

Analysing your manufacturing data can be broken down into four simple steps…

  • Make sure you’re capturing high-quality, relevant data
  • Ditch manual data preparation for modern techniques and solutions such as machine learning and AI
  • Focus on data that will allow your business to grow and scale up
  • Unearth actionable data and leverage it for the result your business needs to flourish and grow

For more information about data analytics in the manufacturing sector, you’re going to want to talk to the experts. DSCallards have been assisting manufacturing companies since 2001 and would be happy to assist you in your data analytic journey. Contact our team today.

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