Apr 15 2014

Balancing Industry Expertise with Client Needs

balancing_industry_expertise_with_client_needsSometimes clients have a very rigid idea of what they want and there’s very little you can do to persuade them otherwise. In these situations, it’s important to remember that though the client’s needs are paramount, you are the one with the expert knowledge. This source of potential conflict can be further challenged when operating in an industry with a client in transformation. For example, what might have been a great deployment plan for a plant-based system might now be different with the migration towards global, multi-site IT systems.

No matter what sector you work in or what service you provide, in most cases the client has hired you because they do not have the knowledge or the means to do it themselves. If this wasn’t the case, then they wouldn’t have hired you in the first place. Don’t be afraid to share your expertise even if it doesn’t fit your client’s exact specifications.

There are some sectors, particularly surrounding creative subjects, where everyone thinks they’re an expert. Design is a particularly good example. Almost every designer out there has a story or two about difficult clients who believe they already know everything there is to know about design despite never having had any training or experience. This can be very frustrating but it is important to remember that you are the expert even when your client is trying to convince you otherwise.

The best way to deal with this situation is to listen carefully to what your client wants, and then make suggestions as to what you would do to improve upon it. Don’t tell them they’re wrong, but make them aware that there are better alternative options. Ultimately, it’s the client’s decision – but it’s your responsibility to share your expertise with them and to try and help them make good decisions.

But what about when your client does actually know what they’re doing? Even when you’re dealing with an industry expert, it’s important to remember that just because they have a clear idea of what they want, it doesn’t necessarily mean that they are not open to suggestions. For example, surface preparation and finishing equipment manufacturer, Airblast AFC, was recently called upon to install two blast rooms for The Rock Island Arsenal Joint Manufacturing and Technology Center – the largest government-owned weapons manufacturing arsenal in the United States. This formidable client had a very detailed, tight specification for their blasting facility but Airblast AFC quickly spotted one major element of the design that they knew could be dramatically improved.

The client had specified an auger screw recovery floor to collect used abrasives, but they were unable to put a pit in the floor. This meant that they would have to have a very high raised floor to fit the system in. Airblast AFC realised that this could be a potential problem. Rather than simply ploughing ahead, they recommended a different option. They suggested that the facility would be much better served by a sweeper recovery floor, which would not only allow for a much lower raised floor (only six inches instead of three feet), but would also provide a more efficient solution all round. Rock Island was happy to accept Airblast AFC’s suggestion, and the installation went ahead.

This example shows the importance of using your expertise even if your client has already decided what they want. In the end, the Airflex floor example, which undoubtedly helped increase the efficiency of the blasting facility, showed how working together can lead to a win-win situation, ultimately creating a better outcome for the client, even though it wasn’t what they’d originally envisioned. It’s in everyone’s best interest to share knowledge you have that could improve the overall outcome for your client. If you have a better solution, share it and in the end the client will thank you for it.


Ella Mason can be found on Google+.

Permanent link to this article: http://www.apriso.com/blog/2014/04/balancing-industry-expertise-with-client-needs/

Apr 10 2014

5 Steps to Proving the Value of Enterprise Quality Management Software

5_steps_to_unlock_value_EQMSProving the value of a software investment takes a well-thought out approach from the beginning, one that starts well before an implementation and continues to measure its effectiveness over time. This becomes increasingly important when we discuss investments in Enterprise Quality Management Software (EQMS), where multiple business units, departments, and regions are all impacted.

As customers only become more demanding, supply chains more global, operating margins tighter, processes more complex, and so on, EQMS suites as well as specific functionalities are quickly becoming a cornerstone of effective quality management. The technology brings together traditionally disparate quality process data and content, transforming the way quality is managed in global organizations.

Although the benefits of EQMS are vast, without an effective way to communicate them, executive support for additional EQMS-related investments and initiatives can easily fall by the wayside. If you’re trusted with a software budget, it’s critical you have a plan in place to validate your decision and even help you attain additional budget for the future. Below is LNS Research’s 5-step plan for doing just that.

1. Benchmark Current Performance in Quality Metrics that Span across the Value Chain

It’s difficult to get a realistic perspective on where you stand without measuring your current performance and then benchmarking it both internally as well as against industry averages. Critical metrics to focus on include the cost of quality, overall equipment effectiveness (OEE), rate of successful new product introductions, product compliance, and on-time and complete shipments.

2. Identify Gaps in Performance and Technology as Compared to Industry Peers

After benchmarking performance, it’s vital that you put together a cross-functional team to dive deeper into those metrics and then identify which operational areas require more resources to get them up to par. This exercise should help to uncover corresponding metrics and technology gaps. For instance, after drilling down into OEE, which is a function of quality, availability, and efficiency, the cross-functional team may conclude the following:

  • There’s no way to easily communicate changes to a standard operating procedure at the global level
  • Manual corrective and preventive action (CAPA) management is hurting quality more than it’s helping
  • The time it takes to identify, communicate, and resolve a manufacturing non-conformance is having a significant negative impact on manufacturing efficiency
  • Current visibility into supplier activities is costly and harming first-time quality in the manufacturing environment

3. Identify and Implement Complementary EQMS Capabilities

With a detailed list of gaps in hand, it’s time to determine which EQMS functionalities will provide the most benefits. You can implement a comprehensive suite of EQMS functionality. Alternately, an approach that’s often taken is to implement specific functionalities that will provide the most benefit and then scale the solution over time as it proves its value. Typical functionalities to consider may include:

  • Compliance Management
  • Supplier Quality Management
  • Risk Management
  • Statistical Process Control
  • Failure Mode and Effects Analysis
  • Complaint Handling

4. Document Improvements

With the solution in place, it’s important to keep a close eye on the improvements delivered. This can be done by comparing your initially benchmarked metrics performance with your current and future performance. Where possible, associate specific improvements to the specific functionalities implemented. If you can prove that instituting a formal risk management program and automating parts of it with EQMS helped to improve the product compliance metrics, additional budget for building out that capability will be easier to secure.

5. Enable a Continuous Improvement Environment

The task of quality management is never complete, and neither is benchmarking. You can enable an environment of continuous improvement by measuring performance and setting increasingly higher goals over time. Market leaders understand this. In the face of today’s tight competition, there’s always room for improvement, and with advancements in processes and technology that bar will only rise higher.   


Those are our thoughts on justifying an investment in quality management software. Please share your own in the comments section below or tweet to me directly @m_littlefield

Permanent link to this article: http://www.apriso.com/blog/2014/04/5-steps-to-proving-the-value-of-enterprise-quality-management-software/

Apr 08 2014

Establishing a Hierarchy Model for Manufacturing Analytics

W_E_Deming_manufacturingW. Edwards Deming was an American statistician, professor, author, lecturer, and consultant. He gained notoriety in the manufacturing world by his extensive promotion of the “Plan-Do-Check-Act” cycle, a strategy to implement continuous process improvement. One of his quotes was “The most important things cannot be measured.” His point was that strategic, long term issues can’t really be measured up front – you don’t know what will be important until time has passed.

In the world of manufacturing operations management, however, I would argue that nothing will improve unless it is measured.

If you are to successfully measure something for improvement, then three conditions must exist:

  1. We must have at least one consistently defined attribute
  2. We must have a way to consistently measure that attribute
  3. We must have a way to compare that measurement, either to a baseline or to a peer attribute

Let me explain with an example. If I have a machine I am responsible for managing, then I need to know the “health” of that machine. Here, an attribute might be “output.” I can quantitatively and consistently measure output quite easily – at the end of the day, my machine produces 20 widgets. But, the question is whether 20 is good?  Should I be producing 25? Or 30? This question can only be answered by comparing my performance to others.

Defining an Attribute

Manufacturers are quite clever in defining and identifying attributes that cast a favorable light on our performance. Nuances best known by those on the shop-floor can be capitalized to help skew performance figures in the most positive light. Regardless, try to be objective and pick a group of attributes that the group can “own” and that are most relevant and applicable. The only possible problem here is if you select too many to measure, thereby diluting your ability to effectively manage these business drivers.

Measuring an Attribute

Here is where manufacturing IT systems come into play. With today’s increasingly global manufacturing operations, no longer is it viable to perform manual measurements – systems must be programmed to perform the necessary calculations. More importantly, these measurements must be done consistently. Here is where a robust analytics platform can be a real benefit, and can make a critical impact on your Plan-Do-Check-Act cycle. Further, a consistent perspective and understanding of the IT systems running in a manufacturing environment is important, so as to not only select the right attribute to measure, but to achieve consistent measurements on a go forward basis.

The following IT systems hierarchy map was prepared by our friends at LNS Research. It is a good illustration of how these systems should be organized, and what role each plays as part of an overall framework of applications running across manufacturing operations.

Establishing a Hierarchy Model for Manufacturing Analytics


With a consistent application architecture or framework, you will now be in a position to best accomplish the last step necessary for continuous process improvement – comparing your performance to others.

Comparing an Attribute

Here is where attention to detail and consistency will either “make” you or “break” you!

If you have bad data as the basis for your measurements, then we all know how that will come out. Now it is necessary to figure out how well you are doing, which can only be accomplished with a comparison – either to your own prior performance, or to that of the industry. Ideally, you can do both. If you have consistently architected your manufacturing IT systems according to your industry’s best practices (such as what is illustrated above), then you are more likely to have results that can be effectively compared to that of your peers.

How do you know if your analytics measurements and strategies are consistent with that of your peers? And, what ways do you have to obtain market performance metrics such that you can effectively compare? One way is to purchase research reports. Another is to attend industry conferences and events, such as the Manufacturing Analytics Summit being held in Chicago on May 21 & 22. Manufacturing Transformation is a media partner for this event, so can offer you 20% (use this code: MFG20).

Regardless of how you collect your market data, be sure to figure out some way to do so. Then, you will have all the pieces for your own Plan-Do-Check-Act cycle, and the sky is the limit!

Permanent link to this article: http://www.apriso.com/blog/2014/04/establishing-a-hierarchy-model-for-manufacturing-analytics/

Apr 03 2014

What the 4th Industrial Revolution is all About

4th-industrial-revolution-HMII recently read an article written by Alex Enderle (@Alex_Enderle) about the 4th Industrial Revolution and how her company (BOSCH ) considered that the real revolution was the business model and not the concept of connected industry.

When we were developing our positioning regarding the 4th Industrial Revolution a few months ago it was clear to us from the beginning that Industrie 4.0 highlighted a part of the 4th Industrial Revolution but that other key aspects needed to be covered as well.

The introduction of smart machines to create smart and connected production, and potentially enable more flexibility and, therefore, more customization is definitely the future of the industry. However, this needs to be combined with two other critical aspects: the Socialization and Servitization of the industry.

In fact, the 4th Industrial Revolution is not only based on technological progress, it is highly inspired by trends that are now part of our day to day lives – including the way we communicate with each other and between machines. Yet, in the 21st century people want to communicate live anywhere at any time with their peers and even with brands. Confronted with an endless flood of information and a need to get things done quickly, people no longer buy a product for its design or cost, but more and more for the services it provides.

  • The two best-selling smartphones would not be as successful without strong operating systems like Android and IOS.
  • Easyjet would not have managed to succeed in the “business trip” market without a strong service offering…
  • Connected machines and factories are tools, just like smart phones. What really matters is how we use them.

This is the reason why we consider that communication and collaboration combined with a strong flexibility and service offering are key aspects of the 4th Industrial Revolution – it helps share new ideas and speed up existing projects, create the best customer experience with customized machines and services, and finally enable greater profit for the company.

The 4th Industrial Revolution is about Social, Smart, Flexible production, with High Value-Added Services. We can help you lead the way!

If you found this article interesting we would be pleased to meet and discuss it with you at our booth at the Hannover Messe from April 7-11. Let’s meet at the Digital Factory Hall 7, Booth D 28. And, as a special bonus for our Manufacturing Transformation readers, don’t worry about the entrance fee – we have free tickets for those interested to attend.

Permanent link to this article: http://www.apriso.com/blog/2014/04/what-the-4th-industrial-revolution-is-all-about/

Apr 01 2014

New Stone Tools Shown to Improve Productivity

apriso1In an interesting twist from the digitization that is now part of how business and manufacturing gets done, one manufacturer is taking a different path – the Stone Age Institute. Researchers there are working on the manufacture and use of stone tools.

Apparently, the selection of an Enterprise Resource Planning system has not even been considered, nor is there a pressing need for other IT systems, automation equipment or robotics. The production process is 100% manual. Current output projections are targeting to have a prototype available soon, but it will only come in one variety, will not have any color choices other than the color of stone, nor will there be any options offered.

Market research has been conducted by Jackson Njau, faculty member in the Department of Geological Sciences at Indiana University and a Research Scientist of the Stone Age Institute and the CRAFT Research Center. So far, work performed at the Olduvai Gorge over the past two decades has provided the competitive intelligence necessary to help ramp up their New Product Introductions schedule, which will be necessary for such a revolutionary new product.

Further, with interests in ecological influences on human evolution, Mr. Njau has conducted actualistic studies, taphonomical and archaeological research in Tanzania since 1994. This research on the natural history and feeding behavior of crocodiles has provided invaluable insight into potentially creating a 3D virtual image to help facilitate the product design and prepare for mass production. This work could lead to a finer understanding of the space environments required to store, manage and maintain these new, innovative tools.

Early testing indicates a strong response and user acceptance by Kanzi, a bonobo chimpanzee, which has been shown to have similar purchase and use behaviors to humans. Initial success in how to best leverage these new products appears promising, indicating the time for ramp up and full production may be soon. See the video and learn more here: http://www.stoneageinstitute.org/tool-behavior.html

Perhaps this might be a turning point away from paperless manufacturing, and a shift toward stone-based communications as well?


Gordon can be found on Google+.

Permanent link to this article: http://www.apriso.com/blog/2014/04/new-stone-tools-shown-to-improve-productivity/

Mar 26 2014

Artificial Intelligence in Manufacturing – Will Watson Work?

IBM Watson as example of artificial intelligence in manufacturingWhat does the factory of the future look like? Much has been written about 21st century manufacturing, where high tech tools and enterprise apps interconnect everything from the supplier to the distributor, leveraging Big Data, manufacturing intelligence and manufacturing operations management (MOM) systems in a sophisticated interplay of information.  Ultimately, the industry is in pursuit of a way to make machines, processes, and products smarter.

But what does that mean? Smart plants, traditionally, have tapped into analytics to extract information from available data. Computers have come a long way in processing power and the programs designed to serve up answers to requests. But it is still based on the 1950s principles of the Von Neumann computing architecture, a rules-based programmatic approach to structured data.

Today, unstructured data, which has no pre-defined data model, (anything from e-mail messages to Word documents to video and social media chatter) is just as important as the numbers in a corporate database. The trick is to capture the unstructured stuff and make it searchable. There’s Big Data, of course, but to truly be intelligent means a computer can’t be bound by logic-based rules of the past.

Instead, the “smart” factory of the future should be using a computing model that is much more responsive. Something that understands natural language and context, and can learn – like a human. According to IBM, manufacturing will need a cognitive machine like Watson – the ultimate artificial intelligence “thinking machine” that appeared on the Jeopardy game show in 2011 and beat two of the show’s biggest champions.

With the formation of IBM’s Watson Group earlier this year, Big Blue announced its commitment to the commercialization of Watson-based apps. To help fuel its efforts, the new unit was given $100 million to invest in third-party software developers, and is making Watson services available in the cloud. Initially, it caught the attention of the healthcare and pharmaceutical industries that are dealing with information overload, which makes accessing relevant content like finding a needle in a haystack. Some healthcare companies, like WellPoint, an insurance provider, are now developing Watson apps that can serve up recommendations for medical services based on a patient’s condition. In pharma, companies are interested in using Watson to help with drug discovery.

And recently, IBM has been exploring how Watson can help manufacturers. According to a NY Times article, IBM researchers began working with Thiess, an Australian contract mining and infrastructure company. It operates a fleet of equipment worth $3 billion, and is looking to Watson to expand predictive maintenance beyond machinery to cover mine operations as whole, factoring in load weights, speed, even weather, terrain, and economic models of mine operations.

Make no mistake, however, that tapping into cognitive technology is no small task. It will require a team of IBM engineers working hand-in-hand with manufacturing IT groups and industry experts to “feed” Watson the information it will need to make decisions.  Much of that information likely resides in industrial control systems, like a supervisory control and data acquisition (SCADA), as well as historians, global manufacturing execution system (MES), even 3D modeling and simulation programs.

In order to succeed, IBM will have to work hand-in-hand with manufacturers and their software vendors, and, in the beginning, be very purposeful about where and how cognitive machines can help the manufacturing industry.

Indeed, it won’t happen overnight, but there’s no doubt that artificial intelligence—whether it’s Watson or something else – has a role in the factory of the future.

Do you agree?

Permanent link to this article: http://www.apriso.com/blog/2014/03/artificial-intelligence-in-manufacturing-will-watson-work/

Mar 18 2014

What’s in an Acronym? An MES or MOM by Any Other Name …

mes_vs_momIn the world of manufacturing, we use a lot of acronyms. ERP, QC, BTO, BOM, DAMA, ISO, MRP, OEE, SCADA, and so on (Manufacturing News and Technology has a long list of acronyms here.) Those of us in the manufacturing business would hardly know how to communicate without the alphabet soup that is manufacturing today!

But sometimes, acronyms get in the way. Every few years it seems a new debate starts over whether a core capability acronym should be reviewed or possibly updated. Lately, I’ve noticed a battle brewing about what term to use when describing the systems that control processes on the plant floor—the piece that sits between ERP and the actual machines. Automation World recently published this article on “MES vs. MOM: What’s in a Name?” and LNS Research just published this article “It’s Really Not About MOM vs. MES: Defining the Space.” Clearly this is a hot topic now!

Some argue that MES (Manufacture Execution System) is the right acronym. After all, that’s what these systems have always been called.

Lately, however, it appears there is now a trend geared more towards the use of MOM (Manufacturing Operations Management). If you are with this group, the argument goes that expectations today have grown to beyond what MES systems have done in the past, and are now geared more towards the management of operations across plants – a wider “footprint,” so to speak. Manufacturers are not just executing production processes one plant at a time anymore; they’re orchestrating the management of operations across a global plant floor with a supply chain that extends to all four corners of the world.

Does it matter? I think it does. We need to agree on terms if we’re going to talk about a subject as complex as manufacturing. If we use the same terms, but mean different things, we won’t be communicating. I know others will argue that the acronym isn’t what’s important, it is the description … but the problem is that if we all use acronyms and not the complete descriptions, then consistency is really needed. Most would argue that there is a clear difference in the meanings of MES and MOM, and this difference affects how people understand the larger issue of manufacturing transformation.

So, in an effort to try and help clarify and provide guidance from the perspective of Manufacturing Transformation, here are our definitions:

MES (Manufacturing Execution System):

This is a shop-floor application that directs the activities of labor, resources and materials to provide the right information at the right time. According to one of our authors, Michael McClellan in his book Applying Manufacturing Execution Systems published in 1997 (ISBN 1574441353), these systems show the manufacturing decision maker “how the current conditions on the plant floor can be optimized to improve production output.” An MES is largely a siloed system, although it can be interfaced (not necessarily easily) to other plants and with ERP.

MOM (Manufacturing Operations Management):

This is a more comprehensive solution that directs more than just the traditional processes on the shop floor, but also other related operations such as warehouse, shipping, quality, maintenance, and labor. In addition, a full MOM solution will offer some sort of visibility into supply chain operations and manufacturing “big data,” so as to deliver decision support in the form of manufacturing intelligence. Although it can drill down to the plant floor, its power is in the aggregated data and larger view of the manufacturing landscape that it provides, whether applied to a single location or to an enterprise. Because it is more comprehensive, MOM:

  • Has access to more data in its architecture, so that means can deliver more intelligence to better support decision makers
  • Readily enables continuous improvement through better tracking and reporting
  • Supports operational agility by making process changes easier and faster to implement
  • Can be more easily linked across multiple facilities, so as to deliver real-time, enterprise views of operations
  • Is effective at helping to identify and deploy best practices across operations – and functions


Looked at this way, one could say that MES is really a subset of MOM. That makes sense, since MOM developed from MES. Stated differently, MES systems tend to comprise plant-based applications; MOM is more of an enterprise solution to manage the larger footprint of manufacturing, whether for one plant or across an enterprise.

More to the point, MOM is an essential capability for the manufacturing transformation currently underway, such as what is now being described as the 4th Industrial Revolution. Industry leaders can’t afford to run every plant as a stand-alone operation, not if they expect to maintain their product quality, adjust to supply chain issues, design-anywhere-manufacture-anywhere (DAMA), and continuously improve.

MES won’t go away. But it seems clear that manufacturers, who think in terms of global performance, quality, and agility, should now be thinking in terms of MOM.

I would appreciate your feedback on the acronym debate … feel free to post a comment below.


Gordon can be found on Google+.

Permanent link to this article: http://www.apriso.com/blog/2014/03/what-is-in-an-acronym-an-mes-or-mom-by-any-other-name/

Mar 12 2014

Mobility’s Impact on the 4th Industrial Revolution

In my last post, I took a closer look at how the fourth industrial revolution is impacting warehouse management activities, as illustrated by a couple of videos showing how Amazon used to manage their inventory and fulfillment processes, and how they it can be done today.

It is important to understand that the previously described scenario could never occur without the technological advances now possible within the mobility movement now underway. Without mobile communications, there is no way devices could speak to others all on their own.

To illustrate the incredible advances that will be possible in the future, it is helpful to look back at the computer revolution, starting back in the 1970s, when we had mainframes first hit the scene. These were amazing machines capable of performing calculations no one even though possible. Then, just 20 years later came PCs in 1990s that could perform 1,000 times the complexity of operations in a structure that was 1/10 the size. Today, tablets and smart devices are now taking the world by storm, with processing power that dwarfs those PCs of the 1990s, in a form factor that is nothing short of stunning.

If you now look at the robotics industry, a similar revolution is now underway. The initial robots were highly specialized, very expensive, and tough to program just “right.” Similar to the mainframe tech era of 1970s, the new trend of today is towards smaller, versatile multi-purpose robots. Now programming a new movement can be done by simply moving an arm in the motion desired – its memory will then instantly retain this action. Two-way communications between robots and production line could then mean new levels of performance, which could bring us the next “tablet” or “smart device” era of innovation.

Another example of how the Internet of Things, as part of the fourth industrial revolution, could impact manufacturing operations is with material replenishment requests. Those factories operating with Lean manufacturing principles have Kanban systems to trigger replenishments of bins, now done manually by shop floor workers assigned specifically to this task. In an automated IoT world, Lean supermarkets or bins could be refilled automatically by machines that move the inventory from the warehouse to the production line. The system already knows what is happening, so doesn’t have to bother showing the humans what is needed – the devices will simply carry out the order all on their own with no human intervention.

Is this a world that sounds a bit George Orwellian? Perhaps. But as they say, necessity is the mother of all invention, and today, we have a whole lot of necessity that is driving some amazing innovation, as part of our desire to expand output, cut costs and improve quality. Time to buckle up for an exciting ride as we transition through the fourth industrial revolution!

Permanent link to this article: http://www.apriso.com/blog/2014/03/mobilitys-impact-on-the-4th-industrial-revolution/

Mar 06 2014

5 Maintenance Tips to Extend Equipment Life and ROI

importance_of_equipment_maintenanceHeavy machinery, especially Mining, Industrial or Farming Equipment, requires constant maintenance to keep it in good working order. Conversely, poorly maintained large machinery equipment runs inefficiently. Breakdowns are costly and safety is also an important consideration.

Here are five top tips for large machinery maintenance:

1. Stay on top of large machinery operator training

Many types of large machinery have multiple operators. One of the ongoing inspections on any checklist should be overseeing the correct operation of the equipment.

Large machinery should be inspected as soon as it is purchased. Operator training is usually done at that point, but training needs to be kept up. Employees come and go, skills become rusty and poor operation leads to breakdowns.

Operator manuals can be revised for the specific work situation. They can be rewritten in simpler language. A short manual can be provided to each operator for easy reference. And, if you operate in a paperless environment, you can rest assured operators use the most current version of each manual.

One other note is to identify best practices, which can then be applied to other facilities or geographic locations. The knowledge you learn about how to maintain your equipment can become quite valuable – be sure to best leverage this important knowledge and use it at every applicable location.

2. Add and test lubricants frequently

Lubricants reduce friction around any moving part. A schedule of good lubrication maintenance extends the life of large machinery equipment and parts.

Lubrication is one of the first and most important of maintenance checks. Look for signs of excess oil or grease build-up on pistons. Check for leaks around oil seals.

Be sure to use the right lubricant. There are specific kinds of oil and grease for every component. Check the manufacturer’s recommendations.

Getting the lubricants checked is a good way to diagnose problems with large machinery. Experts analyze particles in the used oil. The makeup of any contaminants will indicate which part may be suffering from wear or breakdown.

3. Check for signs of wear

Vibration, shock, high temperatures, friction and age all contribute to the breakdown of parts in heavy machinery.

  • Vibration can come from gears and belts that are out of alignment
  • Shock can come from accidents and from poor operator technique
  • High temperatures can come from extended use, friction, poor lubrication and worn parts, among other reasons
  • Age affects many key components. Over time, belts will warp. Seals will dry and crack. Bolts will loosen and stretch out of shape. Age is a factor to monitor in equipment.

Should you discover wear and tear on any moving parts within your heavy equipment, be sure to quickly perform the necessary replacement of any worn parts.

4. Keep large machinery clean, and maintain a clean environment

There are many seals and filters in place on heavy machinery to keep working parts clean and free of contamination. Seals should be inspected regularly to make sure they’re in good condition. Filters should be inspected and changed regularly. Breathers should be kept clean to avoid creating a vacuum in the cab which will suck contaminants into the cab. The electronics in the cab are susceptible to breakdown if contaminated. This impacts the clutch, for example.

Large machinery should be stored in a shed or other building if at all possible. Exposure to wind and weather can lead to rust and rot. The machinery should be run periodically if it is not in use.

5. Have a maintenance and repair schedule, and keep good records

Fluids, tires, tracks and electrical systems are among the components that have to be checked regularly for preventive maintenance. Know what needs to be inspected and when. Here are some examples.

  • Power transmissions have many moving parts that need to be maintained in top condition. Gearboxes need to be checked for lubrication, vibration and damage to parts.
  • Friction materials, seals, gaskets and bearings all need to be inspected for wear and replaced. Gears and shafts usually last a long time and don’t need to be replaced often, if at all.
  • Drive train components need constant monitoring. Check pulleys and v-belts on CVT transmissions for alignment and wear. Check sprockets for correct meshing with chains and for breaks.
  • Test the oil to diagnose problems. Change filters frequently.
  • Bearings keep great amounts of force running smoothly and are vital to large machinery performance. Check bearing lubrication often. Maintaining bearings well extends their life.
  • Lubricate gears frequently.
  • Do a seal check to prevent bearing raceway contamination.
  • Run torque checks on the bolts. Bolts can elongate and creep over time.

To conclude, following the above 5 steps can significantly extend the useful life of heavy machinery, improving the Return on Investment from these important purchases. In today’s global manufacturing world, even greater value can be extracted if you have a global knowledge capture and distribution system such that this knowledge of machinery maintenance can be effectively shared across your organization – letting you reap even greater benefits on a much wider scale.


Author Bio

This is a guest post from Jessica Noonan, who is a freelance writer knowledgeable on manufacturing operations. One of her clients is Statewide Bearings, an Australian supplier of bearings, linear motion and power transmission elements. Got an opinion on something within this article? Connect with Jessica on Google+ to discuss!

Permanent link to this article: http://www.apriso.com/blog/2014/03/5-maintenance-tips-to-extend-equipment-life-and-roi/

Mar 04 2014

How the 4th Industrial Revolution Impacts Warehouse Management

By now I am sure you have heard of the Fourth Industrial Revolution. In Germany, this revolution is being referred to as “Industry 4.0,” and is a common topic of conversation amongst futurists, pundits, analysts and those of us working in the manufacturing industry.

As I see it, my vision of this fourth revolution is for “cyber-physical” production systems where sensor-laden “smart products” tell machines how they should be processed. Business processes will be capable of self-governance across a decentralized, modular system. Smart, embedded devices can then start working seamlessly together by connecting wirelessly – either directly or via either the Internet “cloud.” This Internet of Things (IoT) will then, once again, revolutionize production. Rigid, centralized factory control systems will ultimately give way to decentralized intelligence as machine-to-machine communication hits the shop floor.

Let me give you a couple of examples as a way to help better explain this vision so as to help you see how close we have already become, and how the next steps are really just around the corner.

Warehouse Picking Example

Let’s say I have a pallet I want to move from one location to another in my warehouse. Today, an operator might use a Warehouse Management application, such as what Apriso provides,  to see a list of movement tasks. The system would then identify the pallet to next pick, and then tell me where it is. I would then go to the pallet and scan it to validate, at which point I would take it with my forklift and go to the new location I was instructed by my screen user interface. Once I had made it to the new location, I would then scan a code to validate in the system it was at its new location.

Stated differently, this series of actions are performed to execute the actual movement. What is happening in parallel is a manual synchronization of the real to the virtual worlds so that the data in the system reflects reality.

In the “new” world, you drive up to pick the next pallet as instructed visually by the system, but you don’t need to scan anything. If you are correct, then you won’t hear any alerts. But if your initial guess was incorrect, the forklift would automatically prompt you to choose a different one. Once your destination was achieved, the production line equipment would instruct the forklift exactly where to place the pallet, and then would immediately update the rest of the system that the inventory had been successfully moved. Similar systems already exist and they don’t even require operators. Check out these two videos of Amazon’s picking system:

This video shows how Amazon used to do Warehouse management, which was state-of-the-art in its day.


This video shows the role robots are now playing with warehouse picking activities, and how things have advanced.


In my next post, I’ll take a deeper look at what impact mobility is having on the fourth industrial revolution.

Permanent link to this article: http://www.apriso.com/blog/2014/03/how-the-4th-industrial-revolution-impacts-warehouse-management/

Older posts «