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Anexas a consulting organization based in Denmark with wide presence in India and offices in UAE, Kingdom of Saudi Arabia, Singapore and Canada. Anexas group comprises of Anexas Denmark in Europe, Anexas FZE in UAE, Anexas Consultancy Pvt ltd in India and Anexas Consulting in Middle East, Soon all over the world.

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Next Generation - Artificial Intelligence & Machine learning

Anexas Admin 27-Jul-2017

Artificial Intelligence (A.I.) will soon be at the heart of every major technological system in the world including: cyber and homeland security, payments, financial markets, biotech, healthcare, marketing, natural language processing, computer vision, electrical grids, nuclear power plants, air traffic control, and Internet of Things.

While A.I. seems to have only recently captured the attention of humanity, the reality is that A.I. has been around for over 60 years as a technological discipline. In the late 1950’s, Arthur Samuel wrote a checkers playing program that could learn from its mistakes and thus, over time, became better at playing the game. MYCIN, the first rule-based expert system, was developed in the early 1970’s and was capable of diagnosing blood infections based on the results of various medical tests. The MYCIN system was able to perform better than non-specialist doctors.

While Artificial Intelligence is becoming a major staple of technology, few people understand the benefits and shortcomings of A.I. and Machine Learning technologies.

Machine learning is the science of getting computers to act without being explicitly programmed. Machine learning is applied in various fields such as computer vision, speech recognition, NLP, web search, biotech, risk management, cyber security, and many others.

The machine learning paradigm can be viewed as “programming by example”. Two types of learning are commonly used: supervised and unsupervised. In supervised learning, a collection of labeled patterns is provided, and the learning process is measured by the quality of labeling a newly encountered pattern. The labeled patterns are used to learn the descriptions of classes which in turn are used to label a new pattern. In the case of unsupervised learning, the problem is to group a given collection of unlabeled patterns into meaningful categories.

Within supervised learning, there are two different types of labels: classification and regression.

In classification learning, the goal is to categorize objects into fixed specific categories. Regression learning, on the other hand, tries to predict a real value. For instance, we may wish to predict changes in the price of a stock and both methods can be applied to derive insights. The classification method is used to determine if the stock price will rise or fall, and the regression method is used to predict how much the stock will increase or decrease.

Author :

Santosh Lahane ( Lean Six Sigma Consultant - Trainee)

 

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Lean Six Sigma in Oil and Gas, Petrochemical Industries

Anexas Admin 19-Jul-2017

Lean and Six Sigma has a its broad applications and success stories in oil & gas and Petrochemical industry by using principles of enhanced productivity, safety and environment as well as process quality management in a well-defined framework. It has widely being used in Various Industries and achieved a tremendous results using its statistical tool and techniques, which has resulted a huge reduction in the variance of the process plus the increase in the profit of the organization.

Six sigma with its statistical approach and DMAIC methodology has been implemented successfully in various fields to reduce the number of defects and to bring the quality level in the organization to its expected. Over the past years, the GCC (Gulf Cooperation Council) countries have experienced considerable growth in the oil and gas industry particularly exploration and production (E&P) activities. Oil and gas companies, in the UAE, have implemented an efficient and reliable framework associated with the safety and operational excellence. With new technical advances, cheap extraction of shale oil has now become possible. Hence, it becomes a necessity more than ever, to find an optimum way to stay competitive in the market. The question raised then is: which approach is most suitable or optimum for the framework required and how could it be achieved?

This framework must rely on efficient quality control and assurance methodologies such as Six Sigma, Lean and Kaizen to guarantee a position of being the largest global producer in the oil and gas business. While researching the prevalence of Six Sigma adoption among major oil and gas companies, we were surprised to find that a number of oil companies in the GCC such as, Abu Dhabi Company for Onshore Oil Operations, Abu Dhabi Gas Liquefaction Company, Saudi Aramco, Saudi Electricity Company, Kuwait Gulf Oil Company, Kuwait Petroleum Corporation, Maersk Oil Qatar, Medco Energy, The Bahrain Petroleum Company, etc...) have already established Lean Six Sigma practices in place which are used to address the new challenges they face. Oil and gas companies should be looking to be shielded against barriers imposed by the advent of new shale oil technologies and should also look to boosting their Lean Six Sigma operations, to ensure that full potential is reached as the energy industry is facing its future challenges head on.

Lean Six Sigma has been applied by companies in oil and gas industry to improve production, increase reliability and reduce costs while running safe operations. Too much waste, too much redundancy and lengthy turnaround times result in even the most efficient oil and gas companies failing to meet customer expectations 25-50% of the time. Lean Six Sigma can help in ensuring that customer expectations are met and potential savings of $100millions are realized.  Despite some misconception that some managers have about the implementation of Lean, it will stay the most efficient methodology to apply in the oil and gas business. Success of Lean depends also on top management decisions. The application of these methodologies when applied successfully to projects can produce rewarding results.

Author :

Swaten Tiwari (Lean six sigma consultant - Trainee)

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Six- Sigma- What it is?

Anexas Admin 19-Jul-2017

Six Sigma, the quality improvement methodology made famous by Motorola in the 1980s, has garnered much-deserved recognition in the last few years as more and more companies swear by its effectiveness in improving their bottom lines.

Although Six Sigma methodology was made for manufacturing sector in initial days but these days Six Sigma is widely used in service industry like supply chain, hospitality, banking, IT, ITES, etc. But still there are many companies who stay away from this breakthrough methodology may be because it looks very technical and difficult from outside, but in reality it’s not like that. With the help of few trained people from within or outside the organization (consulting firms), six sigma tools can easily be used in your organization. There is no need to shy from this great methodology which can save you millions. Look at the improvement and saving part.

These days there are various options available to learn six sigma, the popular business improvement methodology, starting from free videos and books available online to the textbooks and various training organizations. But considering the importance of the course one should keep in mind that choosing the right platform for training is critically important. Most of the managers and organizations prefer getting a classroom training from a professional training organization because there you will get to learn more due to certain factors like, personal guidance, experiences of the course colleagues, demo projects, assistance in your project, etc.

From 1987 until 2007, use of Six Sigma, has saved Fortune 500 companies an estimated $427 billion, according to research published by iSixSigma and according to a Wikipedia claim world majors like Amazon, Bank of America, Boeing, CSC, Credit Suisse, Dell, Ford Motors, General Electric are the ones who have been benefited from this great and simple approach.

So, what are you waiting for now! Go and get certified in Six Sigma.

Author :

Himanshu Saxena

 

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Lean and Six Sigma in Healthcare Industry

Anexas Admin 08-May-2017

Dear Friends

It was the same Joseph Juran who linked manufacturing and the healthcare industry; he wrote: as the health industry undertake change, it is well advised to take into account the experience of other industries in order to what worked and what has not. In the minds of many, the health industry is different. This is certainly true as to its history, technology and culture. However, the decisive factors in what works and what does not are the managerial processes, which are alike for all industries.This is the reasoning that allows the principles of lean production and management to be applied in healthcare, despite these being originally developed for application in other industries.

We mentioned that the lean philosophy calls for value creation through elimination of waste. These wastes are common in all industries and are not unique to healthcare. The following is a summary of these wasteful activities:


Overproduction :

Producing something in excess, earlier, or faster than the next process needs it

Inventory :

The cost of managing a large supply inventory may not be obvious at first glance; beside consumption follow-up and space required to store, there is a need to follow expiration dates and to constantly ensure that the items in the inventory are not technologically obsolete. It was already shown that the overall cost of smaller and more frequent shipments is lower than a large-volume purchase for which a discount was provided

Motion :

A lot of walking waste can arise from poor design of the working area

Transportation :

In healthcare this can be evident when moving patients, lab tests, information, etc.

Over-processing :

There are times when material provided to the customers (patients) mandated by regulations can be confusing. For example, multiple insurance claim forms, including ones that are not bills, can confuse the unexperienced novice

Defects :

There are many examples for these defects that can be related to poor labeling of tests, incomplete information in patients' charts or in instructions provided to referrals, etc.

Waiting :

There is not much need to explain why waiting a few hours in line is a wasteful activity

Under-utilizing staff :

Under-use is not only time-dependent but also involves deeper levels such as not sharing knowledge or not taking advantage of someone's skills and creativity; under-use typically shows in hierarchical structures and not using teams.

 

Author :

Alex Rajan ( Senior Manager - Operations and Lean six sigma consultant )

 

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What is Six Sigma ? – An Organizational Perspective

Anexas Admin 08-May-2017

 

A Brief Introduction to Six Sigma

Six Sigma is a rigorous and disciplined process improvement methodology that uses data and statistical analysis to measure and improve any organization’s operational performance. Six Sigma methodology was developed by Motorola in 1986. General Electric (GE), under the leadership of Jack Welch, embraced Six Sigma in 1995 and reported $12bn of savings in their first 5 years.  After observing GE's many successes with Six Sigma, other organizations adopted six sigma methodology for process improvement.

By using this management methodology, companies would be able to eliminate defects in any process. A process is said to have achieved six sigma if it produces 3.4 defects per million opportunities. For a process, defect is considered as anything that is outside the customer specifications.

Six Sigma Methodologies

Mainly two methodologies used in Six Sigma are DMAIC and DMADV. DMAIC stands for Define, Measure, Analyse, Improve and Control and is used for existing processes. DMADV is used for new processes and it stands for Define, Measure, Analyse, Design and Verify. Each phase of DMAIC and DMADV has various deliverables to be achieved while executing a process improvement project. DMAIC methodology helps in reducing the variations in a process by identifying the root causes for any problem and resolving them by implementing the best solution.  DMADV methodology helps to design a new process after analyzing the customer requirements.

                       

 

Six Sigma in an Organisation

An organization usually makes a roadmap for Six Sigma implementation. The roadmap involves the creation of infrastructure, identification of six sigma projects, project group selection and six sigma training, project execution and six sigma implementation. Different people in an organization, when involved in six sigma implementation take up roles and responsibilities as Champions/Sponsors, Process Owners, Master Black Belt, Black Belt, Green Belt and Yellow Belt. Black belts, Green Belts, and Yellow Belts would form project teams and execute six sigma projects.

For the organization, Six Sigma would benefit by reducing Defects (50-90%), Waste (10-60%), Rework, Process cycle times (20-50%) and improvements in Quality, Production Efficiency, Productivity (10-20%), Customer Satisfaction, Capacity, Profitability and Competitive edge.

Six Sigma has proven to be a successful process improvement methodology in industries like Manufacturing, Telecommunications, Banking, Finance, Insurance, IT, ITES, BPO, KPO, Healthcare, Pharmaceuticals, Logistics, Shipping and Supply Chain.

Conclusion:

A company or organization can take best advantage from Six Sigma methodology by providing right training and skills to its employees. Employees who are equipped with Six Sigma expertise and knowledge can solve problems in the best way to enhance productivity and spontaneously this will lead an organisation towards growth and success.
 

Author Bio:

Amitabh Saxena is an award winning lean six sigma trainer and expert. He is the founder and CEO of Anexas Consultancy and loves to write and share his expertise. Over the years he helped and trained thousands of Entrepreneurs, Business Professionals worldwide by providing Lean Six Sigma, PMP, and other professional training.

 

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