Tuesday, 31 October 2017

The Voice of Digital; Shake or get shaken

Blog on Digital Strategy The Voice of Digital; Shake or get shaken

The pace of change in the industry is accelerating. Markets have evolved from a state of organizational centricity, in which manufacturers and service providers largely defined what to produce and market to customers, to one of individual centricity, in which empowered consumers demand insight-driven, customized experiences. And they are continuing to evolve into new forms in which customers, clients and colleagues are becoming active participants rather than passive recipients.

This environment is what we call the everyone-to-everyone (E2E) economy. The E2E economy has four distinct elements: It is orchestrated, based on business ecosystems, which are both collaborative and seamless. It is contextual, in that customer and partner experiences are calibrated and relevant to their specific actions and needs. It is symbiotic, in that everyone and everything, including customers and businesses, are mutually interdependent. And it is cognitive, characterized by data-enabled self-supported learning and predictive capabilities.

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Industry examples such as Uber and Airbnb are great examples of E2E Economy. The entire ecosystem comprises partners who come together to offer seamless experience to individuals like you and me. However, these are orchestrated based on business rules, contextual as customer get information only what he needs to know, Cognitive as the recommendations and pricing is based on deep algorithms that are learning and becoming sharper with time, symbiotic as it is a true power to all as unless all players come together the value will not be delivered to consumers like us.

E2E economy, while directly impacting end consumer industries like Retail, Financial Services and Telecom, it is also significantly impacting B2B business like manufacturing due to advent of technologies like Internet of Things (IoT), Blockchain, 3D Printing.

It has been often said that most of the administrative jobs done by paralegal, paramedical, bankers, etc will be done better using IoT and Blockchain.

It is our belief that no one will remain untouched. Early adopters will benefit the most as it is anticipated that the value for the me-too adopters will diminish significantly. This can be seen from the survey that IBM Institute for Business Value did in 2016. Executives from top performing firms see a higher revenue impact by proactively engaging with ecosystems as compared to average impact seen by executives.

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There is no option but to have a nuanced digital strategy which need to develop new ways of realizing and monetizing value. Initiatives might include spawning new business models, tapping new forms of financing and developing better, more holistic ways of conducting risk assessments.

Shaking in the digital E2E Economy

To set out on the path toward digital, leaders can take four initial steps: envision possibilities, create pilots, deepen capabilities and orchestrate environments.

Step 1: Envision possibilities: Conduct envisioning sessions based on design thinking to produce a definitive reinvention blueprint. For example, through deep conversations and in-depth marketing analysis, develop a better understanding of customer needs, aspirations and desires; brainstorm new ideas to enhance engagement; and visualize unexpected customer scenarios. Incorporate external stakeholders in these sessions, including customers, to encourage thinking that goes beyond business-as-usual.

Step 2: Create pilots: Develop prototypes using agile development, test them with customers and get them to market quickly to promote feedback and iteration. Establish communities of interest to create safe environments to beta test innovations, and incorporate them as a central part of design and development processes.

Step 3: Deepen capabilities: Augment digital capabilities with strategic initiatives, and continue to build and deploy necessary applications aligned to the target digital reinvention operating model and ecosystem strategy. As pilots evolve, impediments around development will emerge, highlighting limitations in existing capabilities. Adopt a continuous, iterative strategy to address these limitations by building new or extending existing capabilities.

Step 4: Orchestrate ecosystems: Embrace a strategy based on holistic reinvention rather than a series of point solutions, maintaining a clear focus on deep needs, aspirations, or desires of customers, clients (such as partners) and colleagues (such as service providers). Focus on ecosystems to expand and align a broader set of capabilities and to help create and deliver on customer promises.

Saturday, 28 October 2017

Internet of Things Application for Metals, Mining and Industrial Product Industries

In the age of digital transformation, Industry 4.0, Internet of things and services (IOT) is at the forefront of realising smarter factory vision. In this blog, I answer three questions What is it ?; Why is it important now? and How metals, mining and industrial product companies can take advantage of this technology ?

What is  Industry 4.0 , Internet of Things?

From 1970s we have employed electronics and information technology (IT) to achieve automation in manufacturing processes. Now, Industry 4.0, IOT makes it possible to integrate entire network of manufacturing process (including smart machines, robots, warehousing systems and production facilities) which can autonomously organize themselves based on predefined KPIs. This enables flexible production, to meet individual customer requirements and profitable lot size of one. These autonomous Cyber Physical Systems (CPS) are the digital model of a given entity, residing in the physical world, which receives real time data from the entity (using sensors) in physical world. It uses advance analytics to assist the entity, communicate with other CPS and direct how to behave.

Why has Industry 4.0 , IOT become important now ?

Three reasons for mainstream application of this technology are

1. Proliferation of low cost, smaller sensors and chips that can be embedded in anything and can communicate over the Internet

2. Advanced analytics capabilities based on big data, statistical and cognitive models

3. Availability of scalable cloud architecture with secure  connectivity, mobile access,  data storage and connected eco-system for managed services deployment

How can metals, mining and industrial product companies benefit with Industry 4.0, IOT?

In order to take advantage of this technology broadly two things are required. First connect and collect real time information and second analyse and interact based on specific data conditions. I take three use case examples below to illustrate these concepts.

Use Case 1: Improve quality in steel industry 

In steel production quality variations occur frequently. Example, in a hot strip mill process data is captured from hundreds of sensors and typically remains in local data historians. Industry  4.0, IOT platform can provide real time availability of this information across all levels and CPS presents an opportunity for autonomous quality correction both on this mill or at the next / previous operation in value chain (possibly done by another company or plant). This platform also helps in predictive maintenance of the mill like abrasion, fatigue of work roll.

Use Case 2 : Drive zero incidents in mining 

In mining operations operator safety is a major concern due to hazardous working conditions (blasting, dangerous gasses and moving equipment). IOT sensors (environment, location, motion and bio sensing) mounted on helmets, jackets of employees are part of CPS and communicate with other mining equipment CPS (Dragline excavators, haul trucks, crushers, LHDs etc) to ensure employee safety.

Use Case 3 : Reduce maintenance costs for windmills 

There are two main failures in windmills, bearing failure and gearbox failure. Typically vibration is monitored but since wind conditions are constantly changing, so different vibration measurement could potentially be at a different speed and load condition. Thus in practice, frequency spectrum pattern is monitored for changes and those changes are related to the type of bearing, machine. Industry  4.0, IOT platform along with CPS can be cost effectively deployed on a large scale to predict windmill failure.

Friday, 27 October 2017

API Days Ahead For Construction

A market in the sharing of information will enable the industry to generate new revenue streams and unlock productivity gains.

At first glance, it might be easy to dismiss a term like Application Programming Interfaces (APIs) as the kind of technical jargon that only software programmers might get excited about.  However, the implications of ‘the API economy’ could barely be less significant as organisations increasingly digitise and become data driven.  In some industries it has even disrupted whole business models and become a regular board room topic.

An API is essentially a means by which different software applications can talk to each other, like a digital glue that can bond disparate systems and services together.

If you have wondered how you can sign up for a new app or website with your Facebook ID rather than entering all of your personal details again, then it is down to APIs. Or perhaps to track a package you simply click a URL in the vendor’s e-mail and it takes you straight to the information in the delivery company’s website without any re-entry of addresses or delivery ID. The You Tube video embedded on a web page, current weather conditions beamed to the home screen on your mobile phone, and price comparison site matching your details to a host of vendor prices in seconds. All made possible by the humble, understated API.

Indeed the chances are that you have not noticed, and that is the point of APIs; that things just work automatically and effortlessly even when you move from one system or service to another.

Open the gates

Software vendors are now realising that their products need to communicate with others. APIs are now so common that anyone can create their own basic event programs without code using services like IFTTT. For example you may wish to create a recipe that automatically switches on the home central heating when your car calculates that you are 30 minutes away.

The largest benefits however are reserved for organisations, where slow and error prone manual handling of information can be replaced by seamless, automated work flows. New, external data sources can be incorporated into organisations’ decision making where, previously, intangibles had to be resolved through gut feel. And organisations can realise latent monetary value in by making it available externally.

But what does this all mean for construction?

Plug in to productivity

The construction industry is highly fragmented and this creates inefficiency. Productivity has barely moved in twenty years and if you can make profits of just 2% then you are doing well. Add to this the fact that the overhead of a major capital project can often represent 20-25% of the total cost, and there is clearly room to divert money from the desk back to the site.

Advances are already being made with the deployment of BIM; federated models such as IBM’s Asset Lifecycle Information Management platform enabling asset information to be assembled from a variety of systems and surfaced to a mobile app or other medium via APIs. This makes a wealth of information available at the user’s fingertips without the need to gather and integrate information manually.

But there are all manner of other ancillary business processes that lend themselves to automation, not least the administration of contracts, in particular the kind of standardised forms of contract found on large infrastructure projects.

Contracts are after all at their heart a series of rules in how to execute obligations and entitlements; so with the right data sources, machine logic can be used to execute certain contractual processes.

And for text based information sources that are not traditionally machine-readable, such as a project communications, we now have cognitive (artificial intelligence) APIs such as IBM’s Watson that can learn, understand and reason with natural language.

They won’t replace a human but they will help the work to be done quicker and better.

Data driven decisions

Connecting to external data can help make fast, informed decisions throughout the lifecycle. Feasibility and design processes can be streamlined through connecting to geological, land value and planning restriction data sources. Commodity price feeds may help estimate project costs more accurately whilst a weather data feed can help plan for inclement conditions.

Monetise your data

What exhaust data does your business generate and would it be of value to a third party?

Making live telematics data from your delivery vehicles available to a project manager on a busy site would help them prepare for delivery with precision, much like Uber helps you catch your taxi. Providing cement curing performance information to the supplier could help them optimise their product mix.

A supplier might provide a feed from their product or service catalogue so that cost can be incorporated dynamically into the design of an asset. And capital project benchmarking data can be made available to clients to help them estimate the cost and duration of building a new asset.

Many shared APIs will just make you a more attractive partner to work with, but some make actually generate new revenue streams.

Reasons to be API

Jealously guarding one’s information in a walled garden is on its way out whilst sharing in a controlled, selective and secure way is on its way in. It may take a while in an industry that is traditionally fragmented and adversarial. But the good news is that everyone stands to benefit.

Wednesday, 25 October 2017

The Future of Metals Industry – Mobility of Everything

Today mobile devices touch each individual. You can find an app for almost everything personal. Enterprises have been slow to adopt mobile applications at workplaces. We still see paper log sheets being filled by pen on shop floor of a traditional steel company. At best an operator reports shift wise tonnages, pieces on a computer terminal. Metals industry has been a slow adopter of Manufacturing Execution Systems (MES) and machine integration is primitive. In this blog I provide insights on how mobile apps at workplace combined with Internet of Things (IOT) will transform this centuries old industry.

Initial use of mobile apps was limited to approvals, alerts, reports, associated workflows using mobile devices. Examples include leave approval, purchase approval, shipment alerts, daily production report.

Today we see sales reps are using mobile apps for customer, account information, capture lead, opportunity, view product catalog, quote price, see movement of metals on commodity markets, report order status, invoice payments etc.

In mills use of handhelds is limited to bar code readers typically for warehouse operations.

IOT refers to connect objects (machines; equipment – furnace, mill; products – coils, slabs, plates) over the internet by providing them with a unique identify. These objects can then sense and respond to environment and share data amongst themselves. Recently we have seen the emergence of low cost, low power single chip micro controllers with built in Wi-Fi, giving us the possibility to develop an entire application on a single chip. Enterprise applications have been fast to adopt and integrate with IOT devices. IBM Bluemix and SAP HANA platform device connector are offering developers the possibility to develop custom applications that interact with enterprise applications.

When we combine mobile applications with IOT devices we get an ever connected world. Sensors on mobile (camera, GPS, accelerometer, barometer) can interact with sensors on equipment’s, products (furnace, mill, plates, coils) and provide a seamless data flow between operator, equipment’s and products. Every computer terminal can be replaced with mobile devices where operators can directly record data like quality parameters, send instructions to machines for corrections, confirm yield, execute logistic movements, identify coils / plates, record visual inspection, trigger maintenance orders etc.

In future each machine will be an IOT device with people fulfilling their roles through apps on their mobile devices. Mobile apps will facilitate ways of working for an individual, role and can even act as the MES system integrating to IOT devices, machines with appropriately developed logic. Let us take one use case from plate mill operations.

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Fig 1 – Role wise mobile application in plate mill

IBM Mobility, IBM Certifications

Fig 2 – Role played by production in-charge

Let us take another example of coil tracking. It has been difficult to deploy RFID tags since steel interferes with RF signals. Using IOT, we can now attach a single chip to coil for accurate identification – improves placement & retrieval in logistics & warehouse applications. A recent use case shown by SAP, included parrot drone being flown for visual inspection for difficult to reach areas and send GPS, sensory data back to enterprise application.

Tuesday, 24 October 2017

Vaadin Bakery: Jump-start your business web app

Vaadin Bakery App Starter is a proven full-stack reference application you can use as a starting point for many serious business web apps. It contains many commonly needed features, like RDBMS database accessed using solid JPA+EJB (or Spring) -based persistency and business layer, mindful authentication and authorization, and a UI code structure suitable for non-trivial, large-scale business applications.
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Example of Vaadin Bakery

No application is the same, and all have different needs. Still, having a proven baseline for you application will help you achieve goals easier and faster. If you don’t need all features, you can easily remove them or replace them with alternative technologies, if required for your use case.

As an experienced architect, you can certainly build these systems from smaller bricks; however, especially if you are starting with a new technology, like Vaadin, having a tested stack gives you much more confidence and can save a lot of wasted time.

Built-in support for running the Vaadin Bakery on Bluemix

The Vaadin Bakery App Starter has two versions, one for a Spring-based stack and another for standard Java EE servers. Bluemix contains my favorite Java EE 7 server (WebSphere Liberty) and various database options, so it is an optimal execution platform for it.

The starter app contains documentation that covers deployment, and it has been optimized for Bluemix-based deployment. If you have created an app using the starter, it contains a CloudFoundry manifest by default with pre-declared services you can use to start your application. The defaults are good for small deployments and testing, but for heavier use, you probably want to configure a more capable execution unit.

If you have already used Bluemix before and have cf tools and Maven installed, pushing the default version to Bluemix can be as easy as the following:

mvn install
cf push

If you are not yet an expert with Bluemix, you can also follow the detailed step-by-step documentation for deploying Java EE to Bluemix.

Tuesday, 17 October 2017

Fixed Asset Accounting in SAP S/4 HANA – A Case Study

We wanted to provide a preview to our Sapphire session being jointly presented with Ambuj, Helene and Alicia from Schlumberger on May 18th. In the presentation coming next Thursday, we will provide Schlumberger specific challenges related to Asset Accounting and how SAP S/4 HANA toolset helped simplify the business processes and developed a tighter integration between Enterprise Asset Management and Financial accounting for assets.

The key is to understand the entire Acquire to Retire value chain of how you use your revenue generating assets and then design your asset accounting processes in conjunction with the Equipment Definition, Activation, Reception, Job Demand to Job Completion and finally Equipment Deactivation.

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Understanding the overall End to End process view allows you to streamline the processes, which in turn Increase the Operational Reliability of the assets and Increase the Asset Utilization directly impacting the bottom line.

It is also pertinent to note that SAP manages the Plant Maintenance/Enterprise Asset Management processes through “Equipment Master” and transactions which are captured against the equipment master like repairs, activation. All the Financial processes are driven by the Asset Master Data which then drives the depreciation posting and asset values in General Ledger. For organizations which use revenue generating assets, we need to synchronize Equipment master and Asset Master. You will learn in the session how we automagically synchronized Asset and Equipment master at Schlumberger.

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Now let us understand how SAP has typically linked the Asset Master Records to Asset Classes, which are then linked to Asset Classes which allow you to define the General Ledger accounts for posting depreciation and acquisition value.  And it has been like that for the last 20 years.

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IBM, SAP S/4HANA, IBM Certifications

Along came S/4 HANA which now gave us the bountiful “Single Source of Truth -Universal Journal”- ACDOCA. This allowed us to have General ledger and Asset accounting in perfect harmony. And by Golly, how wonderful it was to now not have the Asset Accountant and General ledger accountant stop their quibbling over the numbers.

Lot of new functionalities were also introduced at the same time with S/4 HANA introduction.

Now you can enter Accounting principle (i.e. Ledger) at the time of posting the depreciation, which was not possible earlier in SAP ECC.

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IBM, SAP S/4HANA, IBM Certifications

In addition, due to the new architecture of Universal Journal, depreciation was posted by Cost Center and the Asset number. So now the Cost center manager knew which assets hit their cost center. Otherwise there was always your number and my number, which never matched.

Another major improvement was getting rid of Delta Depreciation Areas. Using multiple parallel documents, values are posted correctly from the beginning and Periodic Postings are eliminated, thus avoiding manual reconciliation.

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In Summary, there were significant improvements in S/4 HANA which we will discuss in detail in the session:
  • Reconciliation between General Ledger and Asset Accounting is not required
  • Clean and transparent assignment of depreciation areas to the Accounting Principle
  • Acquisition and Production Costs posting run are not required
  • Balance carry forward is not required by design
  • Planned values are updated online with master data and transaction to assets
  • No need of the delta areas as separate single valuation area per valuation
  • Optional display of Asset view of journal entries
  • Period Close is possible even if there are errors on assets
  • Depreciation values posted in Real time – efficient and faster depreciation run.
  • Depreciation posted for the individual asset and Cost center
  • Depreciation posting run, detailed log option provides information on individual assets level along with cost centers.

Monday, 16 October 2017

Making the Case for Modernization that Works for You

If you work in the complex world of case management like me, you know that digital business relies on how well you work with your content and analyze it…to bring life to customer scenarios, take next best actions and efficiently get the right information to the people who need it. I’m excited and motivated by how managing content and case workflows is continually evolving to be the machine that helps you drive true digital business reach clients in new and different ways.

Friday, 13 October 2017

IBM FAB PowerOps (FPO) Will Soon Get An Uplift

IBM Fab PowerOps (FPO) is a short-term, shop floor area-specific advanced scheduling solution built on top of Real-Time Dispatcher (RTD) targeting FAB throughput, cycle time and equipment utilization improvement and optimization for 300mm semiconductor and TFT-LCD manufacturing FABs. Based on the historical records, for those who have already had a taste of it, a promising 2%+ throughput improvement result in semiconductor FAB Photo area should not be too surprising and out of reach.

The good news is, a new version of FPO will hit the market in mid-2017 with some practical improvements! IBM plans to deliver an upgraded version of FPO before the summer of 2017.  The new version will be version 2.0 (the current FPO version is 1.8) which it would contain several new and improved functions, features, and more advanced optimization logic for better integrated operations, more flexibility, and faster simulation. The features might include at least the following:
  • Multiple Transfer Path Selection
  • Integrated FAB-wide FPO
  • Generic MES Model
  • Stocker Capability Support
With these new features in place, the solution is expected to deal with a more sophisticated manufacturing reality with a higher value in return (compare to its resulting benefits on each run vs. its price tag).

Multiple Transfer Path Selection

Although not to be over-emphasized and over-executed in terms of efficiency consideration, cross-FAB operations do produce a load-balance and cost-saving means from manufacturing operation viewpoint. In terms of cross-FAB operations, current FPO’s optimization support is only limited to optimizing lots running between two manufacturing FABs.  IBM plans to add more special handling logic to support various cross-fab operation cases in a broader way. In version 2.0, lot movement optimization in cross-FAB operations among multiple-FABs (more than two FABs) will become available. The transfer time required along with the constraints and other information of each lot that is put into the cross-FAB list will be computed, compared, and checked against the pre-defined objectives in a more dynamic way. The limitation of this feature would lie on the reality that whether the required lot data and FAB information can be dispatched from Manufacturing Execution System (or other CIM data source) to FPO from both the starting FAB and the destination FAB.

Integrated FAB-wide FPO

There will be one-backbone-to-multiple-area engines configuration and integration available in version 2.0 on top of the current one-backbone-to-one-area engine architecture in version 1.8. Although rare in semiconductor manufacturing cases, this one-backbone-to-multiple-area engines configuration is particularly useful for TFT-LCD Array shop (or also called TFT shop) processes since improving lot movements in one area might potentially shift bottleneck and congestion from that area to the other in most TFT-LCD manufacturing scenarios. Hence, with this configuration,
  1. Multiple-area engines will be linked to a single universal backbone module,
  2. the universal backbone is able to identify and assembly data from MES or other CIM data sources, send formatted data to each area engine for logical computation which includes all the process areas in the FAB,
  3. data sharing among area engines will take place in the backbone with a faster speed for both upstream and downstream optimization computation, and
  4. the summary results for all areas will also be output.

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All area engines in the FAB are connected to one universal Backbone for data capture, assembly, sharing, and output.

Generic MES Model

The Generic MES Model is actually a mini-me, out-of-the-box version of FPO. It will contain a set of basic and ready-to-run FPO functions with a pre-defined data format and schema under the hood. Users can use this Generic MES Model to obtain instant scheduling recommendation results once the actual manufacturing data is input by following its schema and data format. This Generic MES Model is particularly useful in
  1. obtaining quick optimization results without having to spend much time and effort on data preparation,
  2. being used as a scheduling simulator for optimization result comparison among different manufacturing conditions, optimization criteria, and
  3. serving as a foundation platform for further development and enhancement (for those FABs with less complex operation and optimization requirements).
Lots of project time and efforts are expected to be saved by using this Generic MES Model as a starter for FPO implementation, comparing to the traditional FPO implementation approach.

Stocker Capability Support

Lot-stocker information capture, and optimization logic for the lot-stocker information will be added as one of the featured enhancements in the new version. The current lot location projects an impact to scheduling efficiency largely due to the transfer time factor especially for those lots are physically in or around a stocker. Different logical considerations must be applied to obtain the optimization results among different cases, objectives, constraints, and dispatching status. For instance, suppose there is a lot resting outside a stocker and also near by a certain available equipment, is fetching that lot and sending it to that equipment for process produces the best-move result (from optimization point of view, of course)? May be not! There might exist cases and conditions that fetching other lots (may be one of those lots in the stocker), rather than that particular lot resting near by the equipment, might produce a more optimized result if we take other factors, such as scheduling time frame/conditions also into account. This new optimization feature is to be added for TFT-LCD manufacturing scheduling efficiency optimization, primarily.

On top of the new features and functions as described above, three major software tools used by FPO will also get updated which includes CPLEX (from version 12.6.0 to version 12.6.3), JView (from version 8.8 to version 8.9), and Java (from version 1.6 to version 1.8) – will all go into the same package.

Wednesday, 11 October 2017

Choosing The Right Analytics For Your Data

How do you choose the right data analytics for your electronics business?

Corporates in Electronics industry have long strived to understand what’s going on with their operations, clients, industry, market, and even outpace competitions using available data at hand. Data is absolutely critical since it might tell many unknown stories, imply many undiscovered truths, and unseen factors about your business which have not (yet) been realized.

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Thanks to Internet of Things (IoT), as the population of connected devices has grown exponentially, captured data in types and volume have outgrown rapidly in an unprecedented scale. This implies two meaningful results to the Electronics industry players – it provides a chance to obtain a real-time status of “things” in the running business environments (or from other entities in the ecosystem), and it helps companies to retain data in the storage for potential business improvement and new business model exploration. However, unless the captured data is properly and correctly interpreted, analyzed, and applied to gaining business benefits in return, data itself regardless light or dark in nature, large or small in volume, creates only possibilities and opportunities with no business value at all.

Analytic (IBM Analytics) is a common approach (or solution) used to interpret, analyze and drive potential values out of data to gain improvements and benefits. In general, three types of analytics are commonly categorized for discussion:

1. Descriptive – use data aggregation and data mining approach to analyze and tell the insights of the story about “what has happened”.
2. Predictive – use statistics modeling and forecast techniques to predict the potential events and tell “what could happen”.
3. Prescriptive – use optimization and simulation approaches to tell “what should we do” or “what course of actions should be taken” next.

No one analytic is better or worse than another. In fact, choosing an analytic approach all depends on what problems are defined, what business objective and improvement are expected, and for the type of analytics should be adapted to the solution. Some examples can be found in Electronics industry applications:

1. A descriptive analytic might be an excellent choice for analyzing engineering data generated after production for yield improvement. It helps users to attack the possible cause of anomalies through a series of mathematical computations and display of trend, histogram, distribution, and many varying parameter values in manufacturing history that can be traced back to the previous production steps for error correction.

2. A predictive analytic (IBM Predictive Analytics) can be applied but not limited to improving FAB process, manufacturing quality, and equipment maintenance. It is done by building proper mathematical models on particular objects or parameters for real-time input data monitor and comparison. It signals ahead of time before an anomaly actually occurs by showing a weighted possibility of “something might go wrong”.

3. A prescriptive analytic can be found in scheduling optimization applications in the manufacturing industries such as semiconductor and TFT-LCD FABs. IBM’s FAB PowerOps (IBM FAB PowerOps (FPO) Will Soon Get an Uplift) is one iconic solution in this category. In this type of scheduling application, a set of advanced optimization (with simulation) logic is used to analyze the relationships between manufacturing settings, constraints, conditions, and real-time status of running entities (lots, equipment, equipment groups, and reticles). It outputs a series of optimized lot/equipment relationships and associated recommendations such as which lot should be moved to what equipment for process in each analytic cycle to improve throughput and cycle time performance.

IBM has long been offering all three types of Analytic solutions in a wide range of application areas for years and now, IBM is advancing its Analytics path to Cognitive Business and Cloud service featuring IBM Watson (IBM Watson). IBM Watson is a technology platform that uses advanced technology to deal with all structured, unstructured, semi-structured data, and it gives analytic results through “cognitive” steps of understanding, reasoning, and learning the data by natural language(s). IBM has built many references using Watson in various industry applications (i.e. human cancer treatments). Furthermore, a new business group called IBM Watson IoT (Watson Internet of Things) has also been created to offer “Cognitive” analytic applications with IoT capabilities that includes Natural Language Processing (text-to-speech, speech-to-text, and explanation of text/speech from wide range of social media sources), video/audio/image analytics, machine learning, and more.

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One of Watson’s applications in Oncology – helping human cancer treatment

Cognitive analytics such as IBM Watson will continue to evolve. As for Electronics industry application, we expect to see Watson’s cognitive capability on improving overall FAB equipment maintenance efficiency soon.

I will have an in-depth discussion about the application and usage of Watson and Watson IoT technology in Electronics Industry in my next blog post. Until then, “what is the problem we are going to solve?” is the first question must be asked before any analytics could possibly make sense – at the end of the day, everything goes from there.

Tuesday, 10 October 2017

Software Asset Management use case for Blockchain

No doubts we are living on a rapid-changing business environment for electronics and many other industries. The lines between traditional industries disappear, clearing the way clear for new market entrants and fostering the hatching of new ecosystems. Electronics sits at the heart of many of these ecosystems and that’s good news, but it takes a toll: electronic manufactures need to drive further cost efficiency, cut the time to market and look for product differentiation through the introduction of more sophisticated software components.

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the way is clear for new market entrants
As an example, electronic companies are designing connectable products to differentiate themselves and whilst some struggle more than others to succeed, there seems to be one valid premise within the industry: the software piece of the product will bring that “magical experience to the consumer“.

Industry challenges around Software Asset Management

It is not unusual for me to meet people who underestimate the complexity around software asset management (SAM). After all: “you don’t see it, you don’t feel it“. In reality, SAM is very complex due to the intangible nature of the product and also because some recent technology advancements – like cloud hosting or digitization of services – have made software asset management a much more complicated endeavor.

Connectable Products carry license rights from multiple software vendor and staying compliant with all of them is a chimeric task.

The industry challenges around SAM are not trivial at all:
  • Higher dependency on Independent Software Vendors (ISV) and Open source software. Despite the enormous investment OEM’s allocate into SW development, it is almost impossible for them to develop all SW programs. It is a case of fast market readiness and specialization, thus OEM’s need to rely on specialized software vendors to provide for some of the software.
  • Enormous complexity to ensure license compliance. Given the proliferation of software vendors, new business models with exotic charge schemes, SW asset management is becoming more difficult everyday. Each ISV has its unique SKU naming convention, product names, version control rules, not to mention the unique T&C’s embedded in their license agreements and different ways to manage entitlements. Think for  instance the impact in SAM if one of your SW vendor gets acquired by another company and subsequently the SKU, names and T&C’s would change to those used by the acquiring company.
  • Software License accountability through the value chain. Selecting the right ISV is critical to developing great products nowadays and it’s not unusual that one product may contain software from multiple ISV’s. It is imperative to check that all the components in a product are trade compliant with all markets and to establish security and control mechanisms to ensuring that anyone whom may manipulate the product (manufacturing service providers, independent testers, field engineers or even the end user) stays compliant with the multiple license agreements inherited by the existence of programs coming from multiple vendors. The challenge becomes more laborious if we consider the possible breaches of license whilst the product is on the field, caused by changes in the program, like custom code development for instance.
  • The consequences of using 3rd party cloud service providers to host 3rd party software may increase the complexity around SAM.  Like SDN in networking, some of the SW that give live to networking equipment resides in the cloud. The challenge here comes because often SW entitlements are linked to the hardware attributes or how the cloud infrastructure is set up to host that piece of software. Very often cloud service providers may re-arrange the way SW programs are hosted affecting the entitlements.
All these challenges make SAM a very costly and slow process:
  • Multiple parties with conflicting interests around SAM are keeping track independently from each other.
  • The information for effective SAM is scattered into different systems owned by these multiple actors.
  • The process is broken or non-existing so there is no visibility of all transactional updates.
  • Excessive reconciliation workload in managing entitlements, obtaining a true picture of the install base or dealing with SW compliance audits.

Blockchain use case for Software Asset Management

Blockchain is a technology used first in cryptocurrency with enormous potential in business networks and I believe it can make a difference in Software Asset Management:
  • It can effectively assign the SW entitlement to the HW component and link back to the  SW license.
  • It can be used to report the SW installation/removal events to all network participants. Alert when this happens or which participant did it.
  • SW usage information can be recorded into the blockchain, including SW upgrades or the addition of custom code.
The following graphic shows a simplified view of SAM: how it works now (to the left) and how a distributed ledger technology – or blockchain – would orchestrate the process (to the right). The blue blocks represent the original equipment manufacturer main functions involved in SAM. The green block is the end user (OEM’s client) of the product which contains or is serviced with vendor software. Finally the yellow blocks are the two main types of 3rd party agents: Independent Software Vendors and Field Service Providers which often perform the product installations. I’ve not added however the Cloud Service Providers for simplification purposes.

IBM Certifications, IBM Software Asset Management

The benefits of SAM managed through a blockchain technology is:
  1. Process effectiveness through automation (use of smart contracts) and less resources spent in reconciliation, tracking & reporting.
  2. Cost effectiveness out of a better control over SW assets
  3. Increased transparency would enable OEM’s take better portfolio decisions.
  4. Better SAM standards (ISO 19770-1)

Monday, 9 October 2017

Enabling Cross-FAB Operation Capability in MES

It is not uncommon to see the multiple-FAB configuration in modern semiconductor manufacturing site construction that two or more manufacturing FABs are closely built in location with catwalk, pathway, or tunnel linkage to each other (Dual-FAB is most commonly seen). With this specific construction configuration, the shop floors in both manufacturing FABs are inter-connected which provides a much greater production flexibility allowing production lots in one FAB to be moved to the other for processing (this is generally called Cross-FAB operation) before reaching the end-point of the manufacturing processes in some particular layer.

Thursday, 5 October 2017

It’s Time for IBM Datacap Design

It is no secret that IBM Datacap is a robust and highly powerful imaging platform. Using Datacap, one is able to build just about any imaging application imaginable. This can be anything from the simplest of straight forward form capture solutions to the more complex AP, sales orders, medical claims and EOB’s (Explanation of Benefits Form). The power of Datacap is rooted in many ways it can be configured and customized and therefore the need to follow a well-defined process is paramount.

Wednesday, 4 October 2017

Changing Perspectives of Autism in the Workplace

There is a wealth of technical talent available in the population of high-functioning autistic individuals, but it often goes untapped for the want of proper accommodations that could make any workplace – with or without people on the autism spectrum – a better place to work.

Currently in the United States, only 14 percent of those with autism are employed, mainly in a non-professional manner.

Tuesday, 3 October 2017

IBM® Content Manager OnDemand® helps improves Customer Experience

From their phones, watches, tablets, and PCs, your customers demand consistent communications. They demand that their personal information is both secure, yet always available to support their customer experiences. They demand simple experiences without redundant questions or data entry. They demand that you correct the fat finger data entry errors they didn’t notice. They demand clarity in the communications you send to them. They demand convenience in your responses to those communications. In the age of the customer, you either deliver to their high standards for improved CX (customer experience) or lose them as customers.