Tuesday, December 20, 2016

Rogue One – Can Intelligence Prevent Catastrophe?

By Jimmy Asher Director of Product Strategy for Savigent Software

I am fairly sure that you have heard of Rogue One: A Star Wars Story. But just in case you didn’t know, it hit the movie theaters this past weekend. For those less familiar, Rogue One is set just before A New Hope and centered on a new set of characters, who set out to steal the plans to the Death Star. Being a sci-fi fan and having a 12 year-old too, we hit the theater to check it out. 
No worries, no spoilers here – I just wanted to draw some parallels to the latest in the saga and today’s manufacturing environment. So how might this relate to today’s manufacturing environment? Is there a PLM system to govern the building of such a complex piece of equipment? One would hope so – but I will save that for a future blog. Today let’s focus on the underlying plot - it is all about intelligence and doing something with that information. If you are like most, a parallel can be drawn in how the Rebels found, via intelligence, that a massive weapon was being constructed and ultimately how to defeat that weapon – saving countless lives and planets. However, if you are a fan of the dark side (yes, they exist) and root for the Empire – you can instead think of that intelligence as a discovery to a critical flaw in your process. Either way, Rebel or Empire, imagine if you could determine a key defect in your process and take action.

You don’t need to be set in a “galaxy far, far away…” manufacturing intelligence can enable you to better understand your processes and ultimately prevent a catastrophe in your process or business objectives. The heart of manufacturing intelligence is a Historian, a way to capture relevant process data. This is often the logging temperatures, pressures, speeds, etc. in a time-series format capturing the “what” and “when”. Even more critical is contextualizing the “why” and incorporating elements such as batch number, recipe number, operator and status and storing them too. Armed with these fundamental pieces of data, engineers are now equipped to investigate the “how,” should a problem arise. Moving beyond reactive investigation by engineers, systems can be put in place to automatically detect the correlations between events and ultimately turning the data into manufacturing intelligence.

In summary, when armed with the proper intelligence, you can save the galaxy from a threat. But remember, just like characters in Rogue One, intelligence alone doesn’t matter, you need to take action too on what you discover to truly bring about change. Sounds like a topic for a future blog post… in the meantime, enjoy the movie!



Tuesday, November 22, 2016

Investment in Digital Enterprise is Critical for Future Profits

By Jimmy Asher Director of Product Strategy for Savigent Software

A profound digital transformation is taking place within the world’s leading manufacturers. According to a research report released from Pricewaterhouse Coopers (PwC), companies surveyed expect to realize a total of $914 billion related to cost reductions and increased revenues per annum over the next five years. This isn’t simply hype; over 20% of companies are expecting to invest over 10% of their annual revenue in applications and infrastructure to support this goal.

While the upfront design processes are seeing positive impacts – will the remainder of the processes be able to see the same results?

According to the 2016 Global Industry 4.0 Survey: Building the digital enterprise, “40% of companies report that they believe that their product development, engineering and vertical value chains are already benefiting from advanced levels of digitization and integration.” There is no doubt that engineers now have access to a wealth of data that largely has been unavailable to them in the past. One of the elements that I like about this research report is that it is broken down into eight key findings across all processes:

1) Industry 4.0 from talk to action

2) Digitization drives quantum leaps in performance

3) Deepen digital relationships with more empowered customers

4) Focus on people and culture to drive transformation

5) Data analytics and digital trust are the foundation of Industry 4.0

6) Robust, enterprise-wide data analytics capabilities require significant change

7) Industry 4.0 is accelerating globalization, but with a distinctly regional flavor

8) Big investments with big impacts: it’s time to commit

Why is workflow orchestration fundamental to the application of the Industry 4.0?

I believe that workflow orchestration is fundamental to the application of Industry 4.0. What does that mean, you might ask? Workflows are the sequences of action that define the interactions between people, equipment and systems in the normal course of operations, as well as in response to unexpected events. They are the processes and procedures manufacturers strive to define, document and refine in order to improve quality, reduce variability and increase operation efficiency. With the right software, workflows will cut across all eight finding areas. A successful Workflow application should focus on digitizing all processes in an easy-to-understand format rather than locked in reams of customized code or point-to-point applications. Taking the process-first approach will enable agile growth across many areas – which may be different than the traditional thinking of a system-first approach. The study further details a “blueprint for digital success” with six steps to get started, which should be applied to a Workflow approach.

Source: PwC 2016 Global Industry 4.0 Survey

In summary, to capitalize on the predictions identified (and also results that some competitors are likely already gaining) you need to embrace a larger mindset. Industry 4.0 extends integration beyond vertical to the inclusion of customer and supplier needs within your products and services. This can be a large undertaking, but with the applications of different technology tools, such as Workflow, it is very natural and achievable. You should start now to share in the $421 billion p.a. identified by the PwC research report in cost and efficiency gains alone.

Related Links:

Report: http://www.pwc.com/gx/en/industries/industrial-manufacturing/publications/assets/pwc-building-digital-enterprise.pdf

Industry 4.0 Landing Page: https://www.pwc.com/gx/en/industries/industry-4.0.html

Tuesday, September 13, 2016

The Chasm Effect

By Jimmy Asher Director of Product Strategy for Savigent Software

One of the benefits of my position is that I get to spend time interacting with a variety of manufacturers and system integrators. Typically, these conversations revolve around the information divide between the plant floor and the enterprise level. In the past, some of the needs were focused on how to get the orders to the machines on the plant floor or how to get actual consumption data from the machines back without paper. For those of you who like acronyms, topics covered included Manufacturing Execution Systems (MES) and Manufacturing Operations Management (MOM). In the past couple of years a new theme of Smart Manufacturing has emerged. 

Smart Manufacturing and related terms are getting a lot of hype. While I would like to take credit for helping to drive that effort through my articles and posts, I know that it is much more pervasive. The simple truth is that conversations around Smart Manufacturing and digital manufacturing are happening at all levels of the organization – from the CEO to the operators. The fact that you can turn on the TV these days and see a commercial referencing these things is great. 

The downside to this is that hype brings confusion. Because the idea (and hype) of Smart Manufacturing is so grand and often mistakenly thought of as a simple solution, manufacturers are looking to understand how to implement it. However, they’re seeing something that I like to call the “Chasm.” In short, people are approaching Smart Manufacturing as a singular thing and don’t see a clear path to implement it – they see a chasm that they don’t know how to cross. 

Simply stated, Smart Manufacturing is a journey, rather than a singular thing to deploy. I like to paint the mental picture of a series of steps – each with their own discrete items that are very achievable and bring benefits to the organization. To unwind the hype, I suggest that you check out the videos created by MESA. They do a great job of quickly explaining Smart Manufacturing at a high level that might help to drive these conversations within your organization. This series provides an overview with five follow-up videos, each less than three minutes long.  

Monday, June 27, 2016

Smart(er) Manufacturing Is the Next Stage

By Jimmy Asher, Director of Product Strategy for Savigent Software (published by Automation World on June 24, 2016)

No matter what type products that you make, or type of manufacturing you are in, Smart Manufacturing is coming and will change how we think of manufacturing. In some ways, the same journey that industry has been on for years – one of increased visibility and optimization. While these components of technology are accelerating the journey, it isn’t simply technology or its application that makes Smart Manufacturing but rather the changes to the business process that this enables. Smart Manufacturing is about thinking differently!

Read the full version of this column at AutomationWorld.com

Tuesday, May 10, 2016

3 Takeaways From the IndustryWeek Manufacturing & Technology Conference & Expo

Smart Manufacturing sets a new bar.
Nearly every speaker presentation touched on the topic of Smart Manufacturing at last week’s IndustryWeek Manufacturing & Technology Conference & Expo and MESA North American Conference. While it was evident that there are many different definitions for Smart Manufacturing, one thing is clear, manufacturers need to, and already are, investing in new technology to remain competitive. They’re getting “smart” on the topic of Smart Manufacturing in terms of people, processes and technology.

It is time to leverage the Industrial Internet of Things.
OrbitalATK and Synchrono® shared how the global leader in aerospace and defense technologies is Leveraging the IIoT and Visual Factory Technology to Drive Continuous Improvements. Using Synchrono SyncOperations software, powered by Savigent Software, OrbitalATK is able to connect machines, work cells and systems across the enterprise so that relevant data can be collected in real-time and fed into SyncView, a visual factory information system.

With data overload, context is key.

“To measure everything is to measure nothing.”

Advanced Analytics was one of six MESA Smart Manufacturing unConference breakout sessions. The session examined how manufacturers can better use the massive amounts of data they collect on a daily basis. Data alone provides very little value. Smart Manufacturing tools that provide data visualization, advanced analytics and contextual information are what’s needed to transform data into meaningful, timely and actionable business intelligence.

Wednesday, April 13, 2016

APC|M Europe: Driving Decisions with Automated Workflow and R

Mark Gorman of Seagate Technology presented "Driving Decisions with Automated Workflow and R" on April 13 at the 16th Annual European Advanced Control and Manufacturing (apc|m) Conference. The presentation provided an overview of the value and capabilities gained by Seagate using Savigent Software and R.

The rise of automated workflow in the manufacturing industry has lead to a shift in the way companies approach Business Process Management (BPM). Automation of workflow promotes improved operational efficiency, traceability and standardization across an organization. Now it is time for the industry to take automation to the next level.

By incorporating data analysis and contextualization with workflow, companies can extract additional value both from existing infrastructure and from the large volumes of data being produced daily. The benefits of embedding analysis in workflow include faster response speed to events, improved detection and containment strategies and rapid root cause analysis.

Savigent's Platform has been providing workflow automation within Seagate's manufacturing facilities for five years, enabling the manufacturer to tailor an industrial solution that can interact with tools, control systems and Manufacturing Execution Systems (MES) in house. The open-source R programming language has been integrated with the existing infrastructure as an analytics framework. This enables advanced, actionable analytics to be carried out on a scheduled or reactionary basis.

For companies like Seagate, thanks to the use of workflow automation paired with R, root cause analysis is now faster, more targeted and unanchored with all possible contributing factors in the build included. Engineers and technicians are presented with real-time information so that they can take traceable action to address unforeseen events.

How does this work?

Throughout the workflow a summary of statistical differences is created and can be used to take action during production. Depending on the severity of the issue, the platform will prompt a different automated response such as taking a tool out of production, disabling a recipe configuration or holding defective parts. In addition to the ability to drive better decision making in response to unpredicted events, engineers now have visibility over time of their workflow solutions, providing the opportunity for continuous optimization of best practices and improved operational efficiency.

The use of this technology truly empowers engineers and technicians to "work smarter, not harder," and allows manufacturing companies to better leverage their diverse skill sets. This means better compliance and standardization, higher yields, and most importantly, increased profits.

Thursday, April 7, 2016

Microsoft Envision Recap

This week's Microsoft Envision kicked things off in New Orleans with the keynote from the CEO of Microsoft, Satya Nadella.

“It is no longer just about procuring one solution and deploying one solution, it is not about one simple CRM or ERP or even office automation solutions that you get from us or others… it is really about you thinking as a digital company,” stated Nadella.

During the keynote he posed two questions:

1) “How is your business being digitally transformed?”

2) “How is your business model being digitally transformed?”

We are seeing this transformation in manufacturing – the beginning of manufacturing's digital age – where we are seeing a future driven by the Internet of Things (IoT), human friendly automation, additive manufacturing and simulation systems. Manufacturing is no longer seen as the old, dark and slow sector. These topics were discussed in a session called Manufacturing: State of the industry.

In manufacturing, we often refer to this transformation as “Smart Manufacturing”, which is not implying that systems before were unintelligent. Today’s manufacturing is full of technology - IT process, networking and computers.

So is this transformation an evolution or revolution in manufacturing? This question was addressed in a session titled What is a Smart Manufacturer? In reality, it is both! It is an evolution because manufacturers embrace change on a daily basis with continuous improvement by optimizing and improving production and information flow. Smart Manufacturing is the deployment of IT systems to drive these initiatives further than they could yesterday. As for the revolution, there are forces driving change to the core of manufacturing: decreasing time between new products and tailoring products to the desires of their consumers – this drives manufacturers to produce parts in quantities of one versus large runs. For more details, listen to the discussion here.

Thursday, March 31, 2016

Data Visualization and Smart Manufacturing

There is a lot of buzz about the topic of data visualization in the manufacturing industry. Much of the discussion is centered around the necessity of data and the ability to visualize that data in a meaningful way to achieve “Smart Manufacturing.”

But what is Data Visualization?

To some, it is a technology. Software that enables a person to turn copious amount of data into a graphical representation with the premise that it will improve comprehension of a point of view.

To others, it is an art form. Using artistic talent to represent data.

Yet to some, it is a process that one follows to gather and analyze data to inform decision-making.

To me, it is the “Ah Ha” moment, the confluence of all of the above. That moment when the data has been mined, the story has been built, the graphical and pictorial representation has been created, and the exercise has revealed an answer or outcome you could not reach before.

So, data visualization is key to helping manufacturers to use data and analytics in smart decision-making.  Right?

Yes, but here’s the problem: the house of cards hinges on an important concept before anyone can begin to visualize data… context. Visualizing data, or presenting it in a pictorial or graphical format, without context and analysis provides marginal value. It generally provides a one dimensional view without the complete picture.

To better utilize the art, craft and process of data visualization we need to start by setting the scene and determining what question we are trying to answer, or better yet what story we are trying to tell. If you simply ask, “which of my manufacturing lines is performing best?” there are many ways you can answer that question with different data. Is speed the best measure of performance? Cost? Accuracy? The answer is none of the above. To truly measure performance and efficiency you need to analyze all available data, with context, together.

Building context is extremely important for downstream clarity. To build effective context, you need:
·       a way to collect multi-dimensional data, not just data streams coming off individual tools or sensors.
·       a means to determine when is the right time to collect the data validation and a place to store that data and provide early visibility.
·       visibility that enables you to act upon that data and alter your approach if needed.

To think about the problem from another perspective, let’s look at the life cycle of data – from the moment it is produced to the moment it is “realized.” Where does visualization fit in? How do tools and technology assist? Where do we build context?

In the early stages data is produced. Decisions are made about what data to collect, i.e. temperature, humidity levels, power draw, up-time, down-time, etc. At the point of collection, we have the opportunity to provide additional context. What else was happening in the environment when the data was collected? Who was running the machine, what recipes of batches were being made? Now, this collected data starts its transformation into actionable business intelligence.

As we are collecting data, we have the opportunity to look out for other unique events – are we picking up fluctuations in operating parameters, what is happening with other machines running the same recipes or batches, what is going on outside the plant like an abrupt change in the weather? These unique events provide us yet another level of dimensionality to our data.

Now we store the data and begin to analyze. What trends are we seeing, what anomalies are beginning to surface? We start to prove or refine our ideas or hypotheses. We test our assumptions and validate our approach.

Do we need to make changes? If so, let’s adapt our platform or approach and incorporate those changes quickly and efficiently, with minimal impact to operations. Let’s begin the process again, executing the new plan – make the feedback, analysis, and action loop continuous.

Where does contextualization fit in? It is in every stage of this life cycle - helping ensure we have the right data. Setting up visualization enables decision makers to see analysis so they identify new patterns, drill down into charts and graphs for more detail and interactively analyze variable data. When used this way, data visualization can inform almost any decision related to the manufacturing process, from inventory management to maintenance scheduling to human resource allocation.

Together, effective data visualization, and a Smart Manufacturing technology platform can get the right data, in the right format, in the right hands, at the right time, to take the right actions.