Jan 06 2015

The Top 10 Most Read Blog Posts from 2014

Happy New Year! As a way to ring in the new year from Manufacturing Transformation, here is a list of our top ten most read blog posts from 2014. If you haven’t had a chance to read them yet, these might be worth exploring further.


10. Improve Operational Agility with Strong Process Governance


The ability to adapt quickly to change separates the survivors from those destined to extinction. This concept exists in biology, but is equally true in manufacturing operations management, especially in today’s hyper-competitive global market. Just look at the headlines to see examples every day. Companies like HP, Sony and Sharp, which at one time where the leaders in their respective markets are now fighting for their survival. While there might be a situation where too much flexibility led to indecision, my assumption is that every manufacturer seeks to improve their operational flexibility.

9. Welcome to the 4th Industrial Revolution! 


Much was written about the Fourth Industrial Revolution during the year. This article takes a historical perspective on what changes occurred during the past three revolutions, and explores what might be in store for manufacturing in the future, given the future role of machines speaking to each other and the increasing use of intelligence to automate processes.

8. Three Tips for Tracking Inventory with GPS


GPS tracking isn’t just for shipping. It can be used in a variety of ways to track and manage inventory and Work-In-Process at a production site. Using GPS tracking, you can maintain real-time knowledge of where your inventory is both inside and outside the warehouse. You can easily locate it within the warehouse – even if it’s been moved since arrival – and can be instantly notified when it leaves and where it goes.

7. Supply Chain Capability vs. Capacity – What Is best to Optimize?


This article compares supply chain capacity and capability – two different concepts – and what manufacturers should be most focused on for optimization. Supply chain capacity is more of a volume measure – how much throughput can you achieve across your supply chain? Supply chain capability, on the other hand, reflects how robust and agile your supply chain is to disruptions.

6. Five Ways to Measure Operational Excellence 


This post takes a look at what it really means to perform at a level of “operational excellence”? What metrics should be measured? How much should this metric be a comparison? One way to better address this question is to establish a set of criterion as an evaluation metric. A company’s ability to score well on each attribute would suggest a high degree of operational excellence. Read this post to see what criterion might be the best to include.

5. Three Ways to Improve Warehouse Efficiency


When trying to look for ways to improve the efficiency of your warehouse, a good plan is to understand the way that shelves and space are being utilized. This post examines how there are many ways to improve the efficiency of your warehouse such as implementing a warehouse management system), how you position each shelf or how to best utilize space.

4. Six Ways to get Smart and Cut Manufacturing Costs


When it comes to “modern” enterprise manufacturing intelligence, a lot has changed in recent years. Manufacturing issues have only grown more complex, while the new technologies that have evolved to meet these challenges now require new knowledge to understand, implement and leverage effectively. Companies now find themselves under pressure for more rapid product introductions, adaptation to local market conditions and continuous improvement to optimize costs, quality and efficiency.

3. Do Quality Inspections Add Value?


If you choose to not perform a quality inspection during your production process, then some products will be shipped with defects. If this outcome is acceptable, then don’t perform a quality inspection. For the rest of us, this post takes a deeper dive into what should be considered in evaluating the need to perform quality inspections.

2. How do you Improve Production Throughput Capacity?


AGCO leveraged their next generation manufacturing execution system to support and expand their Lean program. After all, you can’t improve what you can’t measure (see related post on this topic here). Read this article to understand how this system is now being used to help make strategic production decisions, as well as to gain better visibility in order to make more informed decisions.


And, the most-read blog post of 2014 was …


1. Three Ways to Improve Quality with Lean Manufacturing


I have been involved in at least two major projects in the past year that involved combining a Lean manufacturing program with quality process improvements, which got me thinking about the combination of the two.


Gordon can be found on Google+ .

Permanent link to this article: http://www.apriso.com/blog/2015/01/the-top-10-most-read-blog-posts-from-2014-2/

Dec 18 2014

Manufacturing Operations: Managing the Robots

iRobot_manufacturingDid you see the original “I, Robot” movie starring Will Smith? Made in 2004, it’s loosely based on the famous robot stories of Isaac Asimov. The premise is that while robots are ubiquitous, they’re not independent; rather, they’re all directed and controlled from a central master artificial intelligence. The movie was pure science fiction, but some of its ideas may be turning into reality in the world of manufacturing.

That was Then

For most of the history of factory automation, equipment control was handled in the machine layer at the local level. Each piece of equipment was programmed locally. When a process needed adjustment, a technician would simply go to the machine and make the change.

This model of automation doesn’t work as well today. Change is much more frequent, and globalization has taken hold as a driving force in manufacturing. In order to manage their distributed operations, enterprises have been embracing a Manufacturing Operations Management or MOM model, where equipment is managed at the process level. This has brought not only more consistent management, but greater agility and responsiveness to change. It’s much easier to launch a new product when all production lines can be centrally managed and improved from a process perspective.

Now this trend is picking up steam thanks to the cloud and a new generation of robot technology.

This is Now

A new report by ARC Advisory Group, “Cloud-based Control and New Industrial Robots,” says that cloud-based control of industrial robots may soon have an impact on manufacturing. The report states that “There is increasing need for flexible production due to shorter product life cycles, increasing product mixes, and ever-changing customer demands.” By controlling robots centrally through the cloud, says the report, manufacturers can overcome problems such as time-consuming configuration, limited scalability, hardware dependencies, and other issues. “Cloud-based control and robots that can be personalized are technological trends that can have significant impact on industrial manufacturing for technology users and suppliers alike,” says ARC.

Naturally, Google is getting in on the act. The company is investing heavily in industrial robots, acquiring robotics firms of various kinds in Japan, the U.S. and Great Britain. Google’s goal, apparently, is to make industrial robots as versatile and easy to use as smart phones. In fact, they talk about “apps” that can be downloaded via the cloud to give robots new capabilities. The company even plans to follow the smart phone model: develop the hardware, intelligence, and some basic apps, and rely on third-party developers to create useful software solutions.

The Future?

Getting back to the Will Smith movie, the centralized control – Artificial Intelligence or AI – turned evil, out of control, and then had to be destroyed. I’m sure we can expect better from our modern manufacturing enterprises, but companies don’t have much time to prepare. According to ARC, these developments are only three to five years away from having a serious impact on manufacturing.

A new generation of robots is coming. Statistic Brain tells us there are 1.3 million robots currently in the world, at least as of February 2014 (source). But it is unlikely these are “IoT” enabled, or can be readily programmed centrally from the cloud or other central server. The question is how many manufacturers will be ready to invest in the next generation of them, and be up for the management task?


Gordon can be found on Google+ .

Permanent link to this article: http://www.apriso.com/blog/2014/12/manufacturing-operations-managing-the-robots/

Dec 16 2014

Taking Lean to the Supply Chain

lean_supply_chainMost large manufacturers today have established Lean or Six Sigma programs for their own operations. It’s practically a requirement to be competitive.

But the line between a manufacturer’s “own” operations, and those of its partners, is getting fuzzier all the time. With today’s increasingly connected supply chains, demand-driven supply networks, and global operations, it only makes sense that big opportunities for performance improvement and cost reduction might be out there in the supply chain, just waiting to be discovered.

The benefits of a Lean supply chain might be a good thing – or might not, depending upon your perspective. But is it realistic? Considering that Lean and Six Sigma programs are all about consistency and control, and involve cultural and operational transformation, can a manufacturer really expect to extend these practices outside of its own organization? And, at what cost?

Pundit Perspective

A new report from Gartner, “Transform Your Supply Chain to Become Demand-Driven,” cautions that creating a Lean supply chain is a journey, and won’t be easy. The authors write, “Companies striving to become demand-driven must recognize that functional integration is a prerequisite — and that it is extremely difficult to achieve. Fewer than 10% of companies that have assessed their supply chain maturity, rate it as integrated.”

Nevertheless, Gartner recommends enterprises pursue the goal, and many are starting to do just that.

Early Signs of Success

A recent article in Industry Week called “Lean into the Supply Chain” describes several examples of global manufacturers who have taken up the challenge, some with striking success:

  • Pratt & Whitney, the aircraft engine manufacturer, aims to triple jet engine production by 2020, with hundreds of suppliers. To keep control, the company has created an “Operations Command Center,” which gathers and shares information about the delivery status of 400 suppliers worldwide, with early warnings if schedules might slip.
  • USG Corp., which produces and distributes gypsum wallboard, joint compound and related construction products, has trained all 100 employees in its supply chain organization in Lean and Six Sigma; the company saved almost $10 million last year while improving operational efficiencies. Says a spokesman, “If we have a warehouse in one region with stock-out problems, we’ll involve production, transportation, logistics, etc., to solve that problem. We’ll use enterprise value stream mapping from several locations throughout the entire process.”
  • MTU America, a Rolls-Royce Power Systems and Daimler subsidiary, created a 400,000 square-foot aftermarket logistics center. They report “huge gains” in on-time delivery and productivity, but say “the biggest accomplishment has been improved customer satisfaction.”
  • Even healthcare, an industry that traditionally has lagged behind in this kind of technology, is “leaning” its supply chain. Intermountain, a non-profit healthcare system of more than 20 hospitals in the southwest United States, opened a 327,000 square-foot Supply Chain Center equipped with the “latest warehousing technology, such as a new warehouse management system, a cubing and dimensioning system, and an automated conveyor system.” They hoped to save $80 million in five years. Instead, they did it in two!


Supporting and enabling all these efforts, of course, is ever-advancing technology that makes it possible for more and more people and operations to communicate and synchronize. As Paul Myerson, professor of supply chain management at Lehigh University, says in the article, “technology not only enables lean but it can help identify and eliminate waste by substituting information for inventory.”

In other words, success with applying Lean manufacturing methodologies across a distributed global supply chain is heavily dependent upon visibility, control and synchronization of material flows such that as issues present themselves, they can be quickly remedied to avoid potential for large disruptions.

Based on the experience of these companies, it looks like information is a lot cheaper to store and manage than inventory. And, it certainly can be transported far more easily!

What do you think? Is your enterprise ready to “Lean into the supply chain”?

Permanent link to this article: http://www.apriso.com/blog/2014/12/taking-lean-to-the-supply-chain/

Dec 11 2014

EQMS: Take it Up Another Notch

EQMS blog postIn my previous blog post, A Compelling Case for EQMS, I discussed the shift of the EQMS (Enterprise Quality Management Software) business case from streamlining and slashing the costs of quality control processes to preventing expensive and embarrassing quality failures. According to an LNS Research report, the cost of quality failures increases exponentially as detection occurs closer in the process to the end user. In a world of complex global supply chains, tracking a quality failure to its source can be a lengthy, expensive, resource intensive undertaking.

Three emerging technology trends promise to add value to the preventive potential of EQMS.

The Cloud

Few trends have shaken up legacy computing like the cloud, allowing organizations to delegate everything from infrastructure to software development platforms and entire software deployments to third parties. There can be agility, scalability and cost advantages to cloud computing for many organizations. For the preventive potential of cloud based EQMS, however, one stands out—extending EQMS reach across the global supply chain.

Early implementations of EQMS added value by centralizing and automating quality control processes across an entire enterprise. In an environment of complex global supply chains, Software as a Service (SaaS) based EQMS implementations can make it much easier for organizations to integrate their suppliers and other partner systems into a single EQMS deployment. It is possible to extend internal systems to partners and suppliers, but SaaS providers can make the process quicker, easier and less expensive – and even make the difference between success and failure – by taking over much of the complexity of management, security and integration. Global providers are also more likely to have datacenters closer to suppliers for better performance and reliability, and the experience and security infrastructure to make sure connections and sensitive data aren’t compromised.


EQMS centralizes and streamlines essential quality control processes such as supplier management, Corrective and Preventive Action (CAPA), compliance management, risk management, complaint handling, change management, and auditing. Add mobile devices, BYOD and mobile EQMS applications, and you have the potential for even more streamlining and workflow acceleration. When an approval is required in a complex workflow or a quality issue or complaint needs to be handled quickly at a higher level, mobile devices and applications make it possible to reach the right parties immediately, wherever they are on whatever device they have on hand. The sooner a quality issue is addressed, the less expensive it is likely to be. Thanks to the Bring Your Own Device (BYOD) to work trend, the mobile device can even be a personal iPhone running a protected corporate EQMS client application. The same goes for partners, suppliers and in some cases even customers.

Big Data and Predictive Analytics

Big data is all about mining huge amounts of disparate structured and unstructured information from multiple systems to discover hidden trends and insights that would normally not be available with traditional data analysis methods. Predictive analytics aims to harness such information to predict and address issues before they have any noticeable impact, or to predict the impact of new initiatives.

EQMS systems are perfect candidates for this type of predictive analytics, as they integrate and exchange information with many other core business systems, potentially even from partners and supplier systems as well. Effective predictive analytics can be invaluable not only for addressing supply chain and regulatory issues before they have a significant financial impact, but gaining invaluable new insight in how quality management processes can be improved.

All of these technologies are in their early stages, so, choosing and implementing the right solution has its challenges. However, as the industry matures and business cases become more widely adopted, the impact on how EQMS can operate is already starting to look very compelling.

Permanent link to this article: http://www.apriso.com/blog/2014/12/eqms-take-it-up-another-notch/

Dec 09 2014

Use a “Digital Twin” to Ensure Products are Built to Design

Use a “Digital Twin” to Ensure Products are Built to DesignI recently published a white paper that takes a closer look at the concept of a “Digital Twin,” and how it can be used to help close the loop between production and design. What follows is a brief extract from the paper. Those interested in reading the full paper can do so here.

Much has been written about the process of transferring the digital rendered designs to the shop floor so the right product is built. The challenge is that quite often what was designed isn’t actually built. Inevitably, issues occur whereby equipment doesn’t perform as planned, incorrect work instructions are used or user errors occur.

The Concept

A virtual, digital equivalent to a physical product, or a Digital Twin, was introduced in 2003 at my University of Michigan Executive Course on Product Lifecycle Management (PLM). At that time, digital representations of actual physical products were relatively new and immature. The information collected about the physical product as it was being produced was limited, manually collected and mostly paper-based.

Virtual products are rich representations of products that are virtually indistinguishable from their physical counterparts. The rise of Manufacturing Execution Systems (MES) has resulted in a wealth of data that is collected and maintained on the production and form of physical products. In addition, this collection has progressed from being manually collected and paper-based, to being digital and collected by a wide variety of physical non-destructive sensing technologies.

Three Parts to the Model

The Digital Twin concept model, as illustrated above, contains three main parts: a) physical products in Real Space, b) virtual products in Virtual Space, and c) the connections of data and information that ties the virtual and real products together. In the decade since this model was introduced, there have been tremendous increases in the amount, richness and fidelity of information of both the physical and virtual products.

On the virtual side, we have much more information now available. Numerous behavioral characteristics can not only visualize a product, but can be tested for performance capabilities. On the physical side, we now collect much more data about the physical product. Actual measurements from automated quality control stations, and data from the machines that produced the physical part, is now readily available to understand exactly what operations, at what speeds and forces, were applied.

Unifying the Virtual and Real Worlds

The amount and quality of information about the virtual and physical product have progressed rapidly in the last decade. The issue is that the two-way connection between real and virtual space has been lagging behind. Global manufacturers today either work with the physical product or with the virtual product. Historically, we have not developed the connection between the two products so that we can work with both of them simultaneously. This shortcoming, however, may soon go away.

In order to deliver the substantial benefits to be gained from this linkage between virtual and physical products, one solution is to have a Unified Repository (UR) that links the two products together. Both virtual development tools and physical collection tools could populate the Unified Repository, creating a two-way connection between the virtual and physical product.

On the virtual tool side, design and engineering would identify characteristics, such as dimensions, tolerances, torque requirements, hardness measurements, etc., and place a unique tag in the virtual model that would serve as a data placeholder for the actual physical product. Included in the tag would be the as-designed characteristic parameter.

On the physical side, these tags would be incorporated into the MES in the Bill of Process creation at the process step where they will be captured. As the processes are completed on the factory floor, the MES would output the captured characteristic to the UR.

The final step would be to incorporate this information back into the factory simulation. This would turn the factory simulation into a factory replication application. Instead of simulating what should be happening in the factory, the application would be replicating what actually was happening at each step in the factory on each product. Many interesting use cases could then be possible by leveraging this digital twin, which could then contribute to improving overall manufacturing excellence.

To read about these specific use cases, as well as further details on this concept, read the rest of the paper here.

Dr. Michael Grieves has published several books on this topic, which can be found here.

Permanent link to this article: http://www.apriso.com/blog/2014/12/use-a-digital-twin-to-ensure-products-are-built-to-design/

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