How to Enable Innovation in Manufacturing with a Commitment to Results - Stefanini

How To Enable Innovation In Manufacturing With A Commitment To Results

In our time, innovation is a matter of survival for some manufacturing companies. Many in the sector continue to face challenges in adopting Smart Manufacturing or Industry 4.0 capability. While there are more technologies available every day, there is no recipe for how to implement these tools. Further, supply chain disruption, aging legacy equipment and pressures to meet heightened customer demand mean there is limited time or resources to implement wide scale changes.

With all of these obstacles, the question of how companies can begin implementing Smart manufacturing capabilities remains unclear. However, what is certain as that manufactures must work towards innovation with a commitment to results.

This concern is as the center of our conversation in the second episode of our StefTalks Podcast.

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What Does Innovation Mean for Manufacturers?

As stated before, innovation is often a matter of survival. While adopting new processes and technologies represents a challenge, failing to begin the process runs the risk of lagging behind competitors who are taking on new capabilities.

The way I see it, innovation is defined by imagination. Breaking this down, imagination means taking the time to imagine creative possibility and then take actions to implement and make the idea a reality on the factory floor.

Innovation can simplify internal processes, making things more efficient. Or it can mean connecting existing systems to create more effective communication and transparency.  Achieving objective means applying technology at the right paint point.

To this end, we see manufactures innovating at 3 levels:

1.      Inter-industry Innovations: This occurs when say an automotive manufacturer sees that a competitor is using a new technology and begins to adopt this technology into their processes.

2.      Intra-industry Innovations: This means adopting innovations, processes or technologies from a different. Famously, there a few examples of aerospace technologies being implemented in industrial logistics to great effect.

3.      Creative Innovations: This means developing and adopting a completely new technology in-house and testing it against existing processes to prove its effectiveness.

At any one time, a manufacturer may have one or all three forms of innovation active in their plant. But how does innovation improve manufacturing operations? What are tangible things innovation brings to a plant?

These questions highlight the concerns many businesses display when resisting innovation efforts. Put simply, the core concern in beginning innovation efforts is the unknown. Manufactures are commonly risk averse, which is no surprise with production lines that follow an exact schedule where even a few seconds of down time can result in waste and costly expenses. But innovation, by definition, always requires that you work with risk and the reality is that some innovation efforts will end in failure.

The key is to adopt a flexible and iterative model that makes consistent, smaller scale changes on existing systems over time. This can also mean stopping a process that proves to be ineffective.

This practice is common in prototyping where models that fail to meet expected metrics are retired. In the short term these moments may mean that time and resources have been wasted. Yet, these moments are ultimately positive, as the decision not to implement innovations that fail to improve the bottom line represents a successful evaluation process, geared toward long term success.

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Practical Steps for Beginning Innovation Adoption

The challenge in recommending common steps in implementing innovation is that no single process will be effective for every factory. For adopting to be successful, we have to account for the unique circumstances of each production line. Adoption should be specific to each company and requires an intimate knowing the type of technologies are already present and the level of digital maturity a company displays.

In practical terms, however, the innovation process should always begin by understanding your own pain points. This requires a robust understanding of a factory’s existing processes, the outputs that drive success, and the areas that display inefficiency.

When determining where to being, choose the area that will bring the most significant results or the path that allows you to invest less money to get started. Either way, adoption efforts should start small and follow an iterative approach. Innovation does not come from a single sprint, but rather is the result several iterative efforts, measuring results and slowly change processes.

Further, it is vital to define the goals and determine a timeline. 10 or 15 years ago, companies would create multi-year plans with closed terms of service and closed outcomes. Many projects were focused on closed scope and closed time frames. Today projects are defined by results.

The former approach has been replaced by more open efforts, where success is defined less by the number of new technologies implemented and more by outcomes or problems that have been solved. Companies are planning less and acting more, but action is underpinned with guidance.

With this in mind, creating smaller scale timelines defined by practical and achievable metrics allows for flexible adoption where what works stays and what doesn’t is tabled.

What are Smart Manufacturing Services? Click here to find out!

Smart Manufacturing & Industry 4.0: From Buzzwords to Process Innovation

Industry 4.0 and Smart Manufacturing as buzzwords have taken on a life of their own. They often seem to promise wide scale upheavals, total revamps of existing equipment in order to make way for, costly high tech smart factories. This creates the impression that innovation process must be wide ranging, presenting an entire reimagining of factory processes and assets. However, the reality that these are simply tools. And there is always the option not to use a tool.

Innovation does not mean simply installing IoT sensors, but for some innovation may simply mean connecting the dots and linking systems that are already in place.  Often adoption occurs while the production line remains in motion. This means adoption should present opportunities for real change while avoiding large scale disruption.  In this sense, Manufactures must follow implementation with a clear commitment to results.

This commitment requires a robust understanding where process inefficiencies are located. Manufactures rely on forecasting to ensure that they will meet expected production numbers for deadlines. Fortunately, this process works both ways as forecasting then helps identify where inefficiencies are located.

In this sense, the true benefits of Smart Manufacturing and Industry 4.0 have more to do with the people present in your organization than the technologies being used. To begin innovating means to leverage the multiplicity of minds present in your organization.

Automation engineers may need to talk with the IT to achieve more efficient data flow. Even for the most manual tasks, user experience can be applied to understand a task and bring tools or information to make that task easier and more efficient. User experience in particular is a strategy common to IT processes, but serves as a new approach to improving process control.

What is the future of Industry 4.0? Click here and read the Supply & Demand Chain Executive article.

Trending Manufacturing Technologies

The human centric approach is vital to long term innovation efforts. However, as adoption proves successful, your team will be working in tandem with new technologies. Consequently, we have highlighted a few technologies that continue to have a significant impact on the manufacturing sector:

Industrial Internet of Things
A series of internet connected devices and sensors, this technology has enabled heightened visibility across the production value chain. This tech is divided into 5 parts:

  • What are you measuring?
  • What network is transferring your data?
  • What data bucket is receiving your data?
  • What intelligence (potentially AI) is being used to send return data?
  • How does this tech interact with human operators?

This is a general overview, but it represents the core questions a manufacturer must answer in order to leverage the technology effectively.

Artificial Intelligence
AI is one of the more widely applicable technologies for the manufacturing sector. This is in large part because success on the production line is determined by real time values and AI systems can quickly convert process data into actionable insights.  However, knowing where AI can be applied is a challenge in its own right. Often the missing pieces are a question of how data insights a being utilized. You may also find more success in finding a partner who can help determine the most useful sites for AI implementation.

While robots have been a regular feature of the manufacturing sector since the 70’s, recent innovations have redefined how they can be used. Larger scale robotic arms are typically protected by a cage and placed in a disctinct zone to avoid injuring human operators. In contrast, Co-bots not designed to replace, but rather to work alongside operators. They are smaller in scale, making it safer for them to operate alongside humans to work in the same space.

Remember, these are all tools and you are never required to use a tool.

Focus on Innovation: Ready to consult with a Stefanini expert?

At Stefanini, innovation is at the core of our DNA. We offer a robust selection of Smart Manufacturing solutions designed to eliminate pain points and strengthen your business’s digital maturity level.

Are you interested in learning how we can quickly and efficiently build the solution for your business? We are here for you. Reach out today!

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