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Dr Ravi M Damodaran,
President—Technology & Strategy,
Varroc

Cover Story Management “Sequencing manufacturing systems”

Dec 23, 2016

“ The sequence of manufacturing systems improvement is extremely important in deciding ROI as this has a direct impact on how prepared are the people to interface with the machines and make the best utilisation of the data generated for efficient running of automated systems” Dr Ravi M Damodaran, President—Technology & Strategy, Varroc

What are the five most essential things, according to you, to make Indian manufacturing industry globally competitive? How is the progress in this area?

Indian manufacturing industry today uses a disproportionately high amount of low-cost, less-skilled temporary labour since we are mostly engaged in lowvalue manufacturing. This results in low productivity and quality as well as high supervisory staff compared to global standards. With increasing cost-pressures, there is a hesitation to staff skilled supervisory staff also. Therefore, most of our manufacturing industries are not in a position to effectively utilise productivity tools (such as Lean Manufacturing, Six Sigma, TOC, etc) to continuously improve operations. Also, there has been little emphasis on game-changing innovation and safety for which we continue to use outdated manufacturing processes that are not very energy-efficient. All these factors have left us poorly prepared for the integrated, automated and connected supply chains (Industry 4.0).

Can you brief us on the various manufacturing principles/ tools & production concepts used in your plants? Can you highlight some of the continuous improvement programmes practiced in your shop floor?

For many years, Varroc has been using TPM, whose effectiveness, however, has been less than optimal due to high content of temporary and less-skilled labour. There is a renewed drive to increase the ratio of skilled labour in the workforce on the shop floor in order to reap the real benefits of TPM across all of our Indian plants. In those plants where the skill level is sufficiently high and disciplined, we have been re-engineering our manufacturing process flows to adapt to automation and digitisation. These activities include interlocking of manufacturing process steps to prevent quality spill-overs from station to station, barcoding to allow traceability of parts in assembly lines and collection of production data directly from machines into ERP systems. In case of our largest customer, we have enabled AutoDx, which allows seamless connectivity of our production planning system to our customer’s scheduling system.

What do you think on the kind of automation or advanced technology strategy that has to be implemented in the shop floors for optimal ROI?

The sequence of manufacturing systems improvement is extremely important in deciding the ROI as this has a direct impact on how prepared are the people to interface with the machines and make the best utilisation of the data generated for efficient running of automated and/or connected shop floors or supply chains. The necessary first step is to re-layout the machine layout and process flow / material flow so as to enable one robot to operate on multiple machines, prior to implementing automation and data collection directly from the machine.

What according to you are the major challenges faced in today’s shop floors? What would be your recommendations for them?

The biggest challenges on the shop floors are the use of a dis-proportionately high number of less-skilled labour and lack of sufficient emphasis on safety. These together are the reasons why businesses are neither in a position to absorb new techniques in manufacturing, nor question the use of inefficient and outdated machines and practices.

How will advance technology concepts boost the productivity and growth in manufacturing industries?

IoT and Industry 4.0 will definitely boost productivity and growth in those manufacturing industries, which are adequately prepared for absorbing these technologies. One needs to shed the low-cost mindset, develop a culture of collaboration between stakeholders, build industrial engineering expertise and infuse Big Data analytics capability in the workforce to complete the preparation. ☐

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