Productivity Management by Industrial Engineers
Productivity Plan - Industrial engineering department has to give an annual productivity plan that specifies the sales growth and reduction in cost giving rise to a planned increase in profit due to productivity improvement.
2025 - A to Z Industrial Engineering - Blogging Theme - Industrial Engineering Benefits the Society and Organizations
Industrial Engineering - Systems/Processes/Methods Improvement Using Engineering solutions creatively.
Industrial Engineering - Prime focus - Productivity Improvement.
Productivity improvement gives National Prosperity and Organization Prosperity.
Source: https://www.linkedin.com/posts/national-productivity-council-gandhinagar_cartoonseriesabr10-productivity-economicgrowth-activity-7301162658278379520-eyyl
A to Z of Industrial Engineering - Blogging Challenge April 2025 - Proposed Posts
https://nraoiekc.blogspot.com/2025/02/a-to-z-of-industrial-engineering.html
Existing Collection of Articles
A to Z of Industrial Engineering - Principles, Methods, Techniques, Tools and Applications
https://nraoiekc.blogspot.com/2018/06/a-to-z-of-industrial-engineering.html
Modern Industrial Engineering - Summary Explanation.
https://www.linkedin.com/pulse/modern-industrial-engineering-summary-explanation-april-kvss-8hiyc
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Productivity Management- Principle of Industrial Engineering
Every industrial engineer is a productivity manager.
He has to plan for productivity and achieve productivity improvement year after year.
As a part of productivity management, he has to assess management actions of the organization for effect on productivity and has to recommend changes if they have an adverse effect on productivity or if there is scope for increasing productivity by modifying them.
Principles of Industrial Engineering, Proceedings of the 2017 Industrial and Systems Engineering Conference, K. Coperich, E. Cudney, H. Nembhard, eds., pp. 890-895.
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Every industrial engineer is a productivity manager.
He has to plan for productivity and achieve productivity improvement year after year.
Productivity Management Related Principles from Literature
Harrington Emerson - Twelve Principles of Efficiency - Productivity Management
1. Clearly defined ideals.
Every organization must have defined ideals that align its employees and guide their behavior. We are today using the terms, objectives, goal, mission, purpose, value etc. for the term ideals used by Emerson.
2. Common sense
Emerson talks of higher level understanding of persons in higher levels of management to promote efficiency.
3. Competent counsel
Efficiency improvement is a specialized knowledge area, and companies have to appoint specialists to develop the efficiency develop function in the organization and take their help in announcing programs and practices.
4. Discipline
The organization has to make plans and run its operations according to the plan.
5. The fair deal
In the organization, every body must perceive fairness in dealings.
Reliable records are required for good plans including good efficiency plans.
What is to be done at each machine needs to be determined by planning department and is to be communicate to the workman.
There needs to be a schedule planned for each machine and operator in the organization based on customer deliveries promised and the associated criteria. Standard times for doing various operations are to be developed to help in developing schedules.
In the organization all facilities and environmental conditions have to be planned to meet specified objectives. A planned facility is termed standard facility.
The movements of machine components, the motions of operators, the transport and handling of materials are to be planned to meet specified objectives.
Standardized conditions and standardized operations are communicated to concerned persons in the organization through standard practice instructions. The efficiency expected will come about only when all activities are performed as per standard practice instructions.
Efficiency improvement has to result in benefit to all involved to sustain it. Employees have to receive efficiency reward as the efficiency in organization goes and the financial benefits are realized.
Productivity Plan - Industrial engineering department has to give an annual productivity plan that specifies the sales growth and reduction in cost giving rise to a planned increase in profit due to productivity improvement.
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As a part of productivity management, he has to assess management actions of the organization for effect on productivity and has to recommend changes if they have an adverse effect on productivity or if there is scope for increasing productivity by modifying them.
Electives to be Offered in IE Curriculum on Improvement of Various Management Systems
1. Financial Accounting System and Improvement
2. Cost Accounting System and Improvement
3. Management Accounting System and Improvement
4. Financial Management System and Improvement
5. Operations Management System and Improvement
6. Supply Chain Management System and Improvement
7. Marketing Management System and Improvement
8. Human Resource Management System and Improvement
9. Project Management System and Improvement
10. Product and Engineering Design System and Improvement
11. Maintenance System and Improvement
12. Construction Management System and Improvement
13. Transportation System and Improvement
I4. Information Systems and Improvement
15. PPC System and Improvement
Role of Benchmarking in Productivity Management
Benchmarking gives the idea of productivity improvement achieved by other companies and thereby forces thinking of IEs to find ways of implementing certain new technologies and management methods in their organizations.
Have you benchmarked productivity improvements of the best Industry 4.0 implementing factories?
478
Bosch Automotive - Bursa - Industrial Engineering 4.0 - WEF - McKinsey Light House Plant
Deployed AI use cases such as close loop process control for hydro-erosion, and upskilling 100% of the workforce.
They reduced unit manufacturing cost by 9% and improved OEE by 9%.
479
CEAT - Halol, India Plant - Industrial Engineering 4.0 - WEF - McKinsey Light House Plant.
CEAT deployed Fourth Industrial Revolution use cases like advanced analytics to optimize cycle times and digitalization of operator’s touchpoints.
The site reduced cycle times by 20%, process scrap by 46%, and energy consumption by 15% .
Overall, this resulted in approximately a 2.5 times increase in export and OEM sales in two years.
480
Dr Reddy's - Hyderabad Plant - Industrial Engineering 4.0 - WEF - McKinsey Light House Plant
The site deployed 40+ 4IR use cases by operating in garage mode and leveraging IIoT & democratized platform for advanced analytics.
It improved manufacturing cost by 43% while proactively enhancing quality and reducing energy by 41%.
481
Ericsson - Lewisville Plant - Industrial Engineering 4.0 - WEF - McKinsey Light House Plant
The use of digital twins led to substantial enhancements: a 25% increase in throughput and a 50% reduction in unplanned downtimes.
482
Foxconn - Shenzen Plant - Industrial Engineering 4.0 - WEF - McKinsey Light House Plant
Shenzhen factory uses computer-controlled autonomous manufacturing in the dark, basically without assembly line workers in the production of electrical equipment components used in smartphones. It is equipped with an automated optimization system for Machine Learning and AI devices, an intelligent self-maintenance system, and an intelligent real-time monitoring system.
The factory’s production efficiency has been increased by 30% and the inventory cycle reduced by 15%.
483
GlaxoSmithKline (GSK) Hertfordshire Plant - Industrial Engineering 4.0
The GSK plant has applied advanced technologies throughout its manufacturing operation, using advanced analytics and neural networks. This has improved line speeds at the site by 21%, cut downtime, increased yields, and delivered an OEE (overall Equipment effectiveness) improvement of 10%.
GSK has applied deep-learning image recognition to detect quality defects, and is using artificial intelligence to optimise machine throughput.
By implementing digital twin technologies, it has boosted capacity by 13%, while cycle time monitoring and the use of digital visualisation tools have cut cycle times by 9%.
484
Haier - Hefei Plant - Industrial Engineering 4.0 - Industry 4.0 WEF-McKinsey Lighthouse
Haier’s Hefei air conditioner factory applied advanced algorithms, digital twins, knowledge graphs and other cutting-edge technologies in the research and development (R&D), production and testing of household central AC systems, resulting in a 33% increase in energy efficiency, a 58% drop in the defect rate, a 49% increase in labour productivity and a 22% drop in unit manufacturing costs.
485
Ingrasys - Taoyuan, Taiwan Plant - Industrial Engineering 4.0 - WEF - McKinsey Light House Plant
By deploying AI use cases across order forecasting, warehouse and production scheduling, product design, quality and assembly-testing domains, Foxconn Industrial Internet’s Taiwan factory has achieved a 73% increase in production efficiency, a 97% reduction in product defects, a 21% reduction in lead time and a 39% decrease in unit manufacturing costs.
486
Johnson & Johnson - Industrial Engineering - Productivity Improvement Activities - Industry 4.0 Lighthouse Plant
Johnson Xi’an replaced its manual facility with a Fourth Industrial Revolution-enabled new factory in 2019. This facility includes digital twins for technology transfer and material handling, intelligent automation of continued process verification (CPV) and batch execution processes.
This has shortened the product transfer time by 64% during site relocation and has enabled a 60% decrease in non-conformance, while improving productivity by 40%, operating costs by 24% and GHG emissions by 26%.
487
K-Water - Hwaseong - REPUBLIC OF KOREA - Industrial Engineering 4.0 - WEF - McKinsey Light House Plant
K-water launched a next-generation AI water treatment plant to reduce production costs, improve responsiveness and reduce human error. It is being scaled across 40+ other sites.
It has helped K-water to reduce its chemical usage by 19%, improve labour efficiency by 42% and reduce power consumption by 10%.
488
LONGi Solar - Jiaxing Plant - Industrial Engineering 4.0 - WEF - McKinsey Light House Plant
Jiaxing site implemented more than 30 Fourth Industrial Revolution use cases, using AI and advanced analytics to boost manufacturing operations.
The site achieved a 28% reduction in unit manufacturing costs, a 43% cut in yield loss and an 84% decrease in production lead time within one year, while also lowering energy consumption by 20%.
489
Mondelēz - Beijing Plant - Industrial Engineering 4.0 - WEF - McKinsey Light House Plant
Mondelez - Sricity
Mondelēz Beijing implemented 38 Fourth Industrial Revolution use cases, such as an AI-powered dough-making lights-off workshop and gas consumption optimization by machine learning. As a result, Mondelēz Beijing has achieved a 28% net revenue growth and 53% increase in labour productivity while reducing GHG emissions by 24% and food waste by 29%.
490
Novo Nordisk - Hillerød Plant - Industrial Engineering 4.0 - WEF - McKinsey Light House Plant
Novo Nordisk has invested in digitalization, automation and advanced analytics, building a robust Industrial Internet of Things operating system to be scaled across their manufacturing footprint, increasing equipment efficiency and productivity by 30%.
491
Procter & Gamble - Takasaki Plant - Industrial Engineering 4.0 - WEF - McKinsey Light House Plant
The site implemented Fourth Industrial Revolution use cases such as data flow integration, digital twin, machine learning across end-to-end value chain (from R&D to customers).
As a a result, the innovation lead time accelerated by 72%, shutdown days for trial were reduced by 21%, and order horizon from customers improved 14-fold.
The plant leverages 4IR capabilities such as data science, AI and machine learning across end-to-end value chain from R&D to retail customers. Altogether, it has been improving productivity and enabling faster reaction to market needs while growing production capability.
492
Quaker Houghton - Industrial Engineering 4.0 - Intelligent Die Casting
493
Schneider Electric - Hyderabad
Over four years, the plant reduced its energy consumption by 59 per cent, improved waste optimisation by 64 per cent, decreased CO2 emissions by 61 per cent, and reduced water consumption by 57 per cent.
To improve energy efficiency and thereby reduce CO2 emissions, the Hyderabad team focused on the highest energy consumers in the plant: air compressors and chillers. An IoT-enabled device, Equaliser 4.0, was installed to regulate the compressors, thereby improving their efficiency. For the chillers, a data-driven energy management system with closed-loop control was fitted to constantly monitor and adjust energy consumption in real-time, optimising energy efficiency.
494
The Coca-Cola Company - Ballina
The site implemented digital, and analytics use cases. As a result, it improved cost by 16% while expanding its SKU portfolio by 30%
495
Unilever - Sonepat
Unilever Sonepat implemented 30+ Fourth Industrial Revolution use cases in its E2E supply chain. Top use cases included boiler and spray dryer process twins, as well as customer data-informed no-touch production planning and inventory optimization.
This improved service by 18%, forecast accuracy by 53%, conversion cost by 40% and Scope 1 carbon footprint by 88%.
496
Western Digital - Bang Pa-In
497
Zymergen - Emeryville
Biotechnology firm Zymergen brought robotics and artificial intelligence (AI) to bioengineering labs, traditionally highly manual sites.
Innovation rates soared, allowing Zymergen to use bioengineering for products previously were not feasible.
For Complete Coverage of Productivity Management Read Lessons.
Modern Industrial Engineering - Productivity Management Module - A Book of Online Readings
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