Centre Of Excellence

Centre For Excellence In Industry 4.0

National Productivity Council (NPC) in association with Asian Productivity Organization (APO), Japan established Centre of Excellence on IT for Industry 4.0 (CoE: IT for I4.0) in June, 2017 with the following objectives:

  • Create Awareness & Develop knowledge base on I4.0
  • Showcase connected industries using I4.0 technologies
  • Disseminate knowledge to various stakeholders

Centre For Excellence In Traning For Energy Efficiency

CETEE is the culmination of Indo-Japanese Governmental Co-operation and has been implemented with the assistance of Bureau of Energy Efficiency (BEE), Ministry of Power, Govt. of India, New Energy Development Organization (NEDO), Govt. of japan.
CETEE aims to achieve these objectives through its state of the art Hands-on Training facility to impart the advanced Energy Efficiency Technology and Techniques in the field of energy efficiency. CETEE is based on "learning by doing" pedagogy where trainees are exposed to "real-industry" projects.

Energy Audit and Efficiency Practical Training and Facilities
CETEE is equipped with the various Industrial Energy Utility equipment designed to demonstrate practically various aspects of energy efficiency opportunities and Energy conservation technique as applicable in industries. Participants themselves can operate the equipments and change the operating parameters to learn the impact of efficient operation, change to energy saving mode, conduct testing for performance evaluation of systems through:

  • Pump Training Facility
  • Fan Training Facility
  • Boiler Training Facility
  • Steam Trap Training Facility
  • Open Burner Training Facility and
  • Combustion Furnace Training Facility

Centre For Excellence In Quality Management

The word quality is often used indiscriminately for many different meanings. Quality can be defined as “fitness for use,” “customer satisfaction,” “doing things right the first time,” or “zero defects.” These definitions are acceptable because quality can refer to degrees of excellence. Webster’s dictionary defines quality as “an inherent characteristic, property or attribute.” QReview will define quality as a characteristic of a product or process that can be measured. Quality control is the science of keeping these characteristics or qualities within certain bounds. In a manufacturing or service environment, there are two major categories of quality: quality of design and quality of conformance. A poorly designed product will not function properly regardless of how well it meets its specifications. Conversely, a product that does not conform to excellent design specifications will not properly perform its intended function.


A quality system is a mechanism that coordinates and maintains the activities needed to ensure that the characteristics of products, processes or services are within certain bounds. A quality system involves every part of an organization that directly or indirectly affects these activities. Typically, the quality system is documented in a quality manual and in the associated documents that specify procedures and standards.

Basic Elements in a Quality System
There are three basic elements in a quality system: Quality Management, Quality Control, and Quality Assurance.
  • Quality Management: Quality management is the means of implementing and carrying out quality policy. They perform goal planning and manage quality control and quality assurance activities. Quality management is responsible for seeing that all quality goals and objectives are implemented and that corrective actions have been achieved. They periodically review the quality system to ensure effectiveness and to identify and review any deficiencies
  • Quality Control: The term quality control describes a variety of activities. It encompasses all techniques and activities of an organization that continuously monitor and improve the conformance of products, processes or services to specifications. Quality control may also include the review of processes and specifications and make recommendations for their improvement. Quality control aims to eliminate causes of unsatisfactory performance by identifying and helping to eliminate or at least narrow the sources of variation. Quality control has the same meaning as variation control of product characteristics. The objective of a quality control program is to define a system in which products meet design requirements and checks and feedback for corrective actions and process improvements. Quality control activities should also include the selecting and rating of suppliers to ensure that purchased products meet quality requirements.
  • Quality Assurance: The term quality assurance describes all the planned and systematic actions necessary to assure that a product or service will satisfy the specified requirements. Usually this takes the form of an independent final inspection. The distinction between quality control and quality assurance is stated in an ANSI/ASQ standard: “Quality control has to do with making quality what it should be, and quality assurance has to do with making sure quality is what it should be.” The quality assurance function should represent the customer and be independent of the quality control function, which is an integral part of the manufacturing operation.


The Seven Basic Tools of Quality (also known as 7 QC Tools) originated in Japan when the country was undergoing major quality revolution and had become a mandatory topic as part of Japanese’s industrial training program. These tools which comprised of simple graphical and statistical techniques were helpful in solving critical quality related issues. These tools were often referred as Seven Basics Tools of Quality because these tools could be implemented by any person with very basic training in statistics and were simple to apply to solve quality-related complex issues.

  1. Stratification (Divide and Conquer): Stratification is a method of dividing data into sub–categories and classify data based on group, division, class or levels that helps in deriving meaningful information to understand an existing problem. The very purpose of Stratification is to divide the data and conquer the meaning full Information to solve a problem.
  2. Histogram: Histogram introduced by Karl Pearson is a bar graph representing the frequency distribution on each bars. The very purpose of Histogram is to study the density of data in any given distribution and understand the factors or data that repeat more often. Histogram helps in prioritizing factors and identify which are the areas that needs utmost attention immediately.
  3. Check sheet (Tally Sheet): A check sheet can be metrics, structured table or form for collecting data and analysing them. When the information collected is quantitative in nature, the check sheet can also be called as tally sheet. The very purpose of checklist is to list down the important checkpoints or events in a tabular/metrics format and keep on updating or marking the status on their occurrence which helps in understanding the progress, defect patterns and even causes for defects.
  4. Cause-and-effect diagram: ( “Fishbone” or Ishikawa diagram) Cause–and–effect diagram introduced by Kaoru Ishikawa helps in identifying the various causes (or factors) leading to an effect (or problem) and also helps in deriving meaningful relationship between them. The very purpose of this diagram is to identify all root causes behind a problem. Once a quality related problem is defined, the factors leading to the causal of the problem are identified. We further keep identifying the sub factors leading to the causal of identified factors till we are able to identify the root cause of the problem. As a result we get a diagram with branches and sub branches of causal factors resembling to a fish bone diagram. In manufacturing industry, to identify the source of variation the causes are usually grouped into below major categories:
    • People
    • Methods
    • Machines
    • Material
    • Measurements
    • Environment
  5. Pareto chart (80 – 20 Rule): Pareto chart is named after Vilfredo Pareto. Pareto chart revolves around the concept of 80-20 rule which underlines that in any process, 80% of problem or failure is just caused by 20% of few major factors which are often referred as Vital Few, whereas remaining 20% of problem or failure is caused by 80% of many minor factors which are also referred as Trivial Many. The very purpose of Pareto Chart is to highlight the most important factors that is the reason for major cause of problem or failure. Pareto chart is having bars graphs and line graphs where individual factors are represented by a bar graph in descending order of their impact and the cumulative total is shown by a line graph.
    Pareto charts help experts in following ways:
    • Distinguish between vital few and trivial many.
    • Displays relative importance of causes of a problem.
    • Helps to focus on causes that will have the greatest impact when solved.
  6. Scatter diagram: Scatter diagram or scatter plot is basically a statistical tool that depicts dependent variables on Y – Axis and Independent Variable on X – axis plotted as dots on their common intersection points. Joining these dots can highlight any existing relationship among these variables or an equation in format Y = F(X) + C, where is C is an arbitrary constant. Very purpose of scatter Diagram is to establish a relationship between problem (overall effect) and causes that are affecting. The relationship can be linear, curvilinear, exponential, logarithmic, quadratic, polynomial etc. Stronger the correlation, stronger the relationship will hold true. The variables can be positively or negatively related defined by the slope of equation derived from the scatter diagram.
  7. Control Chart: Control chart is also called as Shewhart Chart named after Walter A. Shewhart is basically a statistical chart which helps in determining if an industrial process is within control and capable to meet the customer defined specification limits. The very purpose of control chart is to determine if the process is stable and capable within current conditions. In Control Chart, data are plotted against time in X-axis. Control chart will always have a central line (average or mean), an upper line for the upper control limit and a lower line for the lower control limit. These lines are determined from historical data. By comparing current data to these lines, experts can draw conclusions about whether the process variation is consistent (in control, affected by common causes of variation) or is unpredictable (out of control, affected by special causes of variation). It helps in differentiating common causes from special cause of variation. Control charts are very popular and vastly used in Quality Control Techniques, Six Sigma (Control Phase) and also plays an important role in defining process capability and variations in productions. This tool also helps in identifying how well any manufacturing process is in line with respect to customer’s expectation. Control chart helps in predicting process performance, understand the various production patterns and study how a process changes or shifts from normally specified control limits over a period of time.