Star Rapid Is Embracing Industry 4.0

Star Rapid is fully committed to implementing Industry 4.0 practices in order to create a lean and intelligent manufacturing solution for our customers.

Industry 4.0 refers to a system of connected digital technologies. The core principle is that the entire production system is digitally integrated, from incoming raw materials to final inspection and shipping.

This is done by combining continuous improvement methods with smart technologies, automation, wireless sensors and machine learning to reduce waste while enabling more rapid response times. Here is a more detailed look at where Star is headed in 2019 and beyond, and what it will mean for your product development needs.

Kaizen and 6S

Although not new to manufacturing or to Star, the ideology of Kaizen is still relevant and rewards those companies that consistently apply it. Kaizenis Japanese for “improvement” or “continuous change for the better.” To begin to apply kaizen principles, 6S is used to Sort, Shine, Sustain, Safeguard, Set in Order and Standardize.

How do these principles work together? 6S is used to establish and maintain an orderly workplace, clearly labeled and rationally laid out, without clutter or waste. From this, it follows that each employee takes responsibility to consistently apply habits of orderliness and discipline in their daily work. And as orderliness becomes habitual, it inspires the workforce to constantly improve, even in small and incremental steps. Kaizen sets the groundwork on which intelligent manufacturing is built.

Connected Systems

Smart manufacturing places a premium on the collection of large amounts of data in real time. This data is shared between manufacturing cells, processing equipment and operators by being linked to a central computerized database, either via physical cables or wirelessly.

On the shop floor, the Industrial Internet of Things (IIOT) uses various wireless sensors on products to follow individual parts or whole assemblies through their journey in the factory, all the while updating their status to a central database. This creates a cloud of data which provides valuable insights on raw material usage, machine downtime and maintenance, production bottlenecks and more.

So the next step in intelligent manufacturing is to make sure that all relevant devices and products are talking to each other and that this information is available to operators so they can make smart decisions based upon it.

Data Transparency

Once there is an ecosystem of connected devices sharing data, operators can access this information via a variety of terminals, displays or other digital interfaces. From this point of access they see at a glance the status of the task they are working on, and its relationship to the entire product flow.

Operator input at any point in the production cycle will immediately register throughout the system, updating metrics like inventory in stock, machine status and load, product lead time , and any other criteria that management has defined as essential to company performance.

Once a wide field of data can be seen and acted upon, problems become easier to spot and hence easier to correct, for example if parts are spending too long at a given workstation.

All of the above systems are currently in place at Star and are being used to transform our production efficiency. Our task in the coming year will be to combine those systems with automation and machine learning for the next evolution in smart manufacturing.

Automation

Automated systems will be used wherever possible to perform routine jobs. Since automation is repeatable, reliable and tireless, this is the ideal way to free human workers from tasks that would otherwise exhaust them or expose them to potential injury.

Not all automation is of the heavy-lifting variety. Star will integrate automated 3D inspection systems to some processes. This will allow rapid, in-line measurements of fabricated parts and instantly identify non-conformities much quicker than a human operator could do.

Such automated systems will therefore free workers to perform other jobs for which humans are uniquely suited, jobs requiring creative thinking, problem solving, planning and analysis.

Machine Learning

Once a lean system has become digitally integrated, machine learning and artificial intelligence will be combined to anticipate – and respond to – emergent conditions on the shop floor without needing human intervention. For example, CNC milling machines will know how long a given tool has been used to cut metal, and will schedule sharpening or replacement before the tool is allowed to go dull and thereby impact production.

In fact, proactively planning routine maintenance is one of the best ways that companies can prevent costly unscheduled downtime and this system is rapidly being introduced at Star.

Over time, machines will get smarter by using larger data sets to allocate resources efficiently and alert human planners to conditions that may require their input.

Mentorship

Star is addressing the skills gap in manufacturing by launching a mentorship program. In addition to our investment in advanced digital equipment and software, we are also investing in our people so they have the analytical skills needed to make the most of Industry 4.0’s potential. Mentors help to develop skills, reward achievement, share best practices and build confidence among the most passionate team members.

We are excited about these developments as we move aggressively to become a model of lean and intelligent manufacturing in our sector, and we look forward to sharing these advantages with your product development needs.

 

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