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Three Steps to Start the Smart Manufacturing Journey

Three Steps to Start the Smart Manufacturing Journey

The most important thing is to get started. But here are some guidelines to get started transforming your organization.

There has been a lot of discussion about smart manufacturing lately, and many initiatives have turned their focus from manufacturing execution systems (MES) and manufacturing operations management (MOM) to smart manufacturing. However, as I’ve written before, smart manufacturing does not replace any MES or MOM initiative. Just the opposite—MES and MOM are fundamental pillars of any smart manufacturing initiative.

Any vendor proposing a software solution in any way related to manufacturing is now promoting it as a smart manufacturing enabler. MESA International has identified smart manufacturing as one of the key trends in the manufacturing space and is working hard to shape it correctly. The organization has created one of the most comprehensive definitions: “Smart manufacturing is the endeavor to design, deploy, connect and manage enterprise manufacturing operations and systems that enable proactive management of the manufacturing enterprise through informed, timely (as close to real time as possible), in‐depth decision execution.”

Made simple, smart manufacturing is all about making the best decisions in the shortest time based on the most accurate and actual information—whether those decision are made by people, automated machines or cyber-physical systems. This is the foundation for being flexible, effective, responsive and competitive, and for preserving margins.

It looks like it’s not such a big challenge for any company to start a smart manufacturing journey, but in reality it is. Many companies still struggle to identify how to approach the problem and where to start. First of all, I would like to clear the field of a frequent error: A smart manufacturing initiative does not need to be huge project. It can—or perhaps must—start small, but with the right approach. Here are three important suggestions based on my personal experience:

1. The initiative must start at the top of the organization. It’s not a matter of implementing a new technology, or new software. It’s defining a new business strategy that impacts the entire company at all levels and has to be designed correctly and consistently with the company goals. Being smart (or, rather, smarter) is nothing absolute; it really depends on which direction the business is moving and what challenges it faces. Based on the strategic vision, a company must define its organization and the effective processes to coordinate the organization. Only after this is the technology chosen to support the processes and empower the organization.

2. Start small from the most sensitive areas. Analyze the most significant pains and start there to get the fastest and biggest benefits. Solving 80 percent of the full problem typically costs 20 percent of the full cost, while optimizing the last 20 percent is the most expensive part. Do not think that any type of system you put in place will last for 20 years. It’s not old-style automation where an asset performs the same task for years and years; it’s all about adapting to market changes and demands and being flexible. Your business strategy will adapt probably every five years or less, and the organization and technological systems you have implemented will need to be updated and adjusted as well. They are part of a formal or informal continuous improvement initiative, and they will need to be continuously improved. For this reason, keep them lean and do not over-sophisticate them.

A smart manufacturing initiative does not need to be huge project. It can—or perhaps must—start small, but with the right approach.

There are many stages in a smart manufacturing initiative, and their sequence depends a lot on the maturity level of the company. The final goal will be a fully integrated enterprise—from the shop floor to the strategic enterprise resource planning (ERP) level and along the full supply chain—but today’s goals will be simpler for most. Real-time data collection, MES implementation and manufacturing intelligence dashboarding could be places to start to implement and measure the results.

3. Start from people. Consider that no matter where you start and no matter which technology you adopt, it will impact the organization and the people. It will change the way they operate and will require some time for adoption. If you choose an area that brings them obvious and easy benefits, they will immediately buy into the initiative and support it. The more you automate production and enable automatic decisions at any level, the more people are required to elevate their role and contribution and make more complex decisions. Smart manufacturing is not about replacing people; it’s about focusing on people to empower them as much as possible to provide the intelligence that the machines or software cannot guarantee. In smart manufacturing, people become more important, not less.

The critical thing is to take the first step quickly. With a pilot project or with a more complex and impactful project, it’s important to buy the ticket and start the journey. In the digital era in which we live, there is no option. Companies can choose to change and evolve or be overtaken by more agile players that can be totally disruptive to the marketplace.

Luigi De Bernardini is CEO at Autoware, a certified Control System Integrators Association member based in Vicenza, Italy. For more information about Autoware, visit the Autoware profile on the Industrial Automation

source: https://www.automationworld.com/three-steps-start-smart-manufacturing-journey

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Moving From Dumb Manufacturing to Smart: Catching the Fourth Wave

Use Smart Manufacturing to close the information gap between the shop floor and the office floor.

Charles Horth | Jan 27, 2017

This is the third of my three posts on moving from dumb manufacturing to smart.

In the previous blog, we discussed Waves 1 and 2; this one will cover Waves 3 and 4. The four waves are layers--each builds on the one before.

Collectively, they drive first-time-right quality.

Wave 3: Improve quality management with centerlining

Traditional quality management measures outcomes--end products. Is the chocolate donut the right weight? Does the car door close properly? Are the tissues the right size?

But the flaw in this system is readily apparent--by the time you detect quality problems, you’ve already squandered time and resources on making flawed products.

By monitoring inputs rather than outcomes, centerlining takes a more proactive approach. The idea is to control the key parameters in the input, thereby run to target, and achieve the right output--do the right thing, consistently and continuously. Monitor what comes in, to gain consistency in what comes out.

Of course, you cannot eliminate quality measurement of finished products--particularly those, such as pharmaceuticals, with intense regulatory requirements.

But by decreasing the variability of key inputs, centerlining considerably decreases waste. Not to mention the amount of time spent dealing with isolated islands of data that arise from log sheets and lab data. As well, centerlining enables efficient short orders, and the ability to run a variety of products through the same equipment.

Leveraging the 80-20 rule

As always, the 80/20 rule rules: by determining the best settings and ranges for the important variables and eliminating variance in a handful (say 20%) of parameters, you can decrease 80% or more of errors. Think of it as a pre-emptive quality strike! 

And returning to the theme in the first of these three blogs, centerlining is one of the ways that smart manufacturing moves from art to science. In order to achieve that perfect cake, the oven temperature must stay between x and y, the flour must weigh between p and q, and so on. It’s measured, it’s digital, it’s scientific.

Still in its infancy!

Yet while most leading companies have adopted centerlining, the majority of manufacturers have not, certainly not to any significant extent. It’s far from uncommon in plants to have three shifts that have three ways of making a product--basically the definition of dumb manufacturing.

Centerlining never stops

The thinking is that if there’s a discrepancy or variation in output, there’s a reason, and the reason should be attended to. Proper centerlining is ongoing, allowing for changes in equipment, raw materials, or any other factor.  

Wave 4: ERP integration

Wave 1, visibility, is about connecting to the shop floor control systems. Wave 4 is about connecting to the business systems: e.g. ERP / SAP / Oracle.

Simply put, ERP systems exist to count money--not kilos or production numbers. Your ERP tells you what you want the plant to do: how many widgets to make, and when. Your MES (Management Execution System) tells you, in real time, what was actually done. What you produced, what materials you used, how much was wasted.

But until you have connected these two, you’ll be scheduling manually (and yes, using an Excel spreadsheet is still manual). Plus doing material management manually. In a world that keeps moving faster, your reaction time is slower, not to mention based on less accurate information.

Catching Wave 4 offers many business benefits--you will:

• Reduce overruns and under-runs
• Ensure right (released; matching Bill of Materials) material is being used
• Ensure right amount of material is delivered to lines at right time
• Ensure that schedule updates are communicated quickly to lines
• Ensure that lines can still run if ERP is off-line for prolonged period of time
• Provide detailed traceability from ingredients through to finished goods.

Once you connect your MES with your ERP, you’ve closed the schedule integration and material management loop. In fact … you’ve closed the gap between the shop floor and the office floor.

Now, you’re closely linked with your customers. You receive an order; the plant produces based on the information in the order; the output is shipped and invoiced. With the fourth wave, your opportunity to deliver the right thing, at the right time, profitably, takes a giant leap forward.

In summary

Smart Manufacturing--enabled, expanded and extended by the Internet of Things--merges operation with information technology. It enables insight in real time, and action, allowing everyone on the shop floor to base decision-making on readily available information.
The four waves I’ve described are the roadmap to get there.

Charles A. Horth is the CEO of Factora, a company of manufacturing consultants who use software to help factories achieve their full potential by raising the visibility of key information on the shop floor so that plant management, employees and company leadership can run more efficient manufacturing systems.

Moving to Smart Manufacturing: Your Plant is Talking to You!

Here's how to catch the first two of four waves necessary to begin implementing smart manufacturing. Part two of a three-part series.

Charles Horth | Dec 22, 2016

Some customer’s words not only stick with you, they shape your thinking forever after.

Many years ago, on a plant tour, a Brazilian pulp plant manager turned to me and said: “Can you help me understand the language of the mill? My mill is talking to me and I can’t understand. And my people can’t either.”

As discussed in my recent article, in the days of "dumb" manufacturing many people worked in the plant, but only a handful held mastery. That mastery was at least as much art as science, and it involved dealing with the actual machines.

Smart manufacturing means dealing with a digital clone of the machines.

Rather than managing physical assets or operational technology, we’re managing a digital clone that we create, through informational technology. We can manage the machines when we’re nowhere near them.

How do we do that – how do we get to smart manufacturing? By catching four waves--just like a surfer. In this and my next article, I’m going to discuss these four waves. And the first wave is--actually, no. I’m going to start with Wave 0. Here we go…

Wave 0: Enablement

Traditionally, the people who manage the control networks in the plant are a constrained resource. They’re not available to make the data available, and this is no accident.

Because control engineers were the gatekeepers. If they didn’t isolate and protect the control networks, minor changes would have major impacts on operations. Not good! 

This meant you could have 15 lines, run by 15 isolated networks--15 fiefdoms. Because if you had only one control system for 15 lines, any glitch would bring them all down.

And that’s the mentality that many control engineers were raised in. 

But there’s nothing today that prevents us from connecting these fiefdoms to a wider network to share information.

So the enabling phase of smart manufacturing is to harness IT expertise to bridge this gap. Plus, convince the control people to give up their hard-won ownership. Remembering that IT and Control aren’t always the best of pals…

It’s never a walk in the park; you have to get two divergent groups, with different goals and fears, working together. But if you don’t have this enablement, you have nothing.

If you don’t catch Wave 0, you won’t catch any of the others.

Wave 1: Visualization

Visualization is the ability to actually see what’s going on! And it’s valuable to a wide range of people--operators, lab technicians, supervisors, engineers, and managers. So aim to get that data into as many hands as possible. 
Visualization shows you:

• What is running, what is not
• What is in maintenance, what is not
• Which orders are running, which are not
• Scheduled attainment
• Percentage waste on each line.
• Last but far from least, what is trending … allowing users to quickly see cause and effect and find relationships between measurements.

Plants talk best in visual. And it’s worth the effort; visualization can cater to and elevate the productivity of every stakeholder.

I remember a meeting where a Process Engineer spoke up to say: “We can save disk space by only storing the data when the machines are running--it’s the only data we care about.” Up spoke Maintenance: “But we want the data where the machines are not running so we can calibrate the instruments!”

Visualization solves this one:

• Accounting sees total consumption numbers, to determine cost of raw material consumed.
• Maintenance sees stoppages and breakdowns--no matter how minor.
• And so on and so on.

Visualization delivers value and enables action, in real time. Better yet, visualization allows you to ask questions you’d never even thought of before.

Wave 2: Efficiency

Now you have visualization, you can begin to hone in on efficiency.

Downtime may be the best example of what you’ll see better with smart manufacturing, and of how that leads to increased efficiencies. Tracked by a clipboard-toting humanoid, you miss a lot. Not only that, human-gathered data is suspect.

Continuing with downtime as an example, with smart data:

• You can identify and change unproductive patterns, e.g. multiple small stops. You’ll see the ones that are invisible to human eyes, the ones that never get recorded, but have a considerable negative influence on performance.
• You enable root cause analysis. You’ll find out the top three (or five, or ten) reasons why you’re stopping, and the cost of those stops. And that’s the basis of continuous improvement.
• Going beyond downtime to the big picture, you’ll know, with accuracy, where your energy is going, how much waste you are generating per line, and when you have rate loss. Armed with this information (rather than the often-biased guesses pre-smart manufacturers have to make) you can make the right choices to improve efficiencies and performance.
• Everyone begins to speak the same language, there’s one version of the truth, because you get context around your KPIs. Rather than “the machine went down,” it’s “the machine went down on Charlie’s shift, on work order 257, customer 8.”
• Often, a friendly competition over KPIs develops between lines and shifts, leading to improved efficiency, engagement, and morale. Not bad!

That was Waves 1 and 2! Tune in to my next article for Waves 3 and 4, the last two to catch to get to Smart Manufacturing.

Charles A. Horth is the CEO of Factora, a company of manufacturing consultants who use software to help factories achieve their full potential by raising the visibility of key information on the shop floor so that plant management, employees and company leadership can run more efficient manufacturing systems.

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Digital Economy / Ekonomi Digital

Digital Economy / Ekonomi Digital

Apa itu Ekonomi Digital? Ketika membahas tentang ekonomi digital pasti tidak jauh dari beberapa hal berikut :

1. Proses digital yang bersangkutan dengan transaksi
2. Dampak yang terjadi karena digitalisasi yaitu
   a. Manfaat atau positif adanya digital economy, contohnya adalah dengan menggunakan ekonomi digital maka keuntungan yang dihasilkan akan semakin meningkat sesuai dengan strategi yang digunakan.
   b. Ekses/residen atau negatif adanya digital economy, contohnya adalah pada suatu tempat tertentu fasilitas tidak memadai untuk ekonomi digital dan itu akan membuat penurunan penghasilan dalam perekonomian ditempat tersebut.

Ketika melakukan ekonomi digital ada beberapa hal yang sulit untuk dilakukan dalam mewujudkan digital economy tersebut, antara lain :

1. Fasilitas yang tidak memadai
2. Ketidaktahuan tentang cara penggunaan
3. Kenyamanan berdasarkan kebiasaan dengan menggunakan media tradisional, contoh kasusnya adalah seorang petani sudah mempunyai fasilitas untuk melakukan digital economy, namun karena lebih nyaman dengan kebiasaannya maka petani tersebut tidak menggunakan digital economy, hal ini berkaitan dengan kondisi psikologis dari para petani yang mayoritas tidak begitu paham dengan adanya teknologi dan menutup diri dengan hal tersebut.

Beberapa hal yang ada dalam digital economy yaitu :

1. Persaingan, jelas sekali dalam ekonomi digital persaingan akan terus bertambah berdasarkan dengan kemudahan dalam penggunakan digital economy tersebut
2. Teknologi, dengan menggunakan media sosial dapat menunjang tingginya popularitas seperti kepercayaan atas jasa yang diberikan.
3. Budaya
4. Sumber Daya Manusia dalam hal ini manajemen
5. Regulasi atau birokrasi dari suatu sistem

Berikut adalah ciri-ciri ekonomi digital beserta penjelasan singkat :

1. Disintermediation, yaitu tidak adanya perantara, namun sekarang berubah menjadi reintermediarible yaitu adanya perantara seperti market place, jasa antar, dan lain sebagainya
2. Molekulisasi, yaitu perubahan pada struktur atau birokrasi yang digunakan
3. Berbagi no language
4. Prosumption, yaitu seseorang yang berada pada posisi produsen sekaligus konsumen juga
5. Discordance, yaitu dampak negatif dari ekonomi digital
6. dan masih banyak lagi

Kesimpulan :

Jadi Pengertian Ekonomi Digital adalah aktivitas atau kegiatan ekonomi yang lebih menitikberatkan pada sarana digital dan mempunyai dampak pada perekonomian yang harapannya bisa meningkatkan keuntungan bagi yang melakukannya.

Digital Economy Rankings 2016 GCI (Global Connectivity Index)

sumber: https://www.susantokun.com/definisi-digital-economy-ekonomi-digital-indonesia/