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ASPECTS OF MACHINING CENTRE DEVELOPMENT Improving machine performance with technical expertise

Nov 28, 2022

The uncertain consumer market situation for the past couple of years have forced industries to justify the purpose of market existence by focusing on redefining their R&D strategies. The piece explains a technology perception of all the three aspects of machining centre development at BFW. - Dr Harshad Sonawane, Head- Research and Development activities, Dr Kalam Centre, Innovation, Bharat Fritz Werner (BFW)

The Dr Kalam Centre for Innovation of Bharat Fritz Werner has been playing a significant role with the clear objective of adding value to the current portfolio of BFW products and technologies since 2016. A team of about 10 research engineers, comprising doctorates and several masters and bachelors degree scientists with diverse specialisations is dedicatedly striving to achieve the common goal of technology and product enhancement. The Indian government (DSIR) recognised research centre’s output in general, which is evaluated in the form of manifestations of new products, new and advanced technologies, new verticals/businesses, international paper presentations/publications, and patents.

Technical pillars of innovation

The BFW R&D’s innovation theme comprises four major technical pillars:

  1. Spindle

  2. Structure

  3. Technologies

  4. Sustainability

The R&D centre has dedicated technology skills and the resources to cater to all these technical aspects of the machine tool business. Let us discuss a technology perception in all of the above aspects of machining centre development.


BFW categorises spindles into three major aspects based on their technology of development and usage: a widely used belt-drive spindle, a highly efficient in-line spindle, and a high-speed motorised spindle for die-mould applications. Recently, R&D has played an important role in the spindle variant reduction from 121 to the final 12 numbers of spindles based on the standardisation of spindle components and applications.

A spindle expert system has been introduced for spindle designers, where the system suggests suitable spindle combinations based on the spindle speed, torque, and power requirements. It also serves as a decision-making tool where the priority will be assigned to various dependent and independent aspects such as dynamic stiffness v/s balancing, accuracy v/s cost, low thermal effects v/s noise, etc. The expert system uses all these input data based on priority ratings and helps predict suitable drive type, bearing type, and bearing span using python-based algorithms. It ultimately saves time and reduces dependency on individual spindle experts.

An air-oil lubricated motorised spindle to realise high-speed machining (HSM) has been fabricated and is being tested for its performance at vertical as well as horizontal positions. The high-speed spindle is designed to attain spindle speeds up to 20,000 RPM from existing 10,000 RPM capabilities. A high-performance high-speed air-oil lubricated spindle has been designed for the upcoming precision series machines.


The FE analysis tool helped BFW designers optimise the existing machine designs and introduce new structural designs for the machining centers. BFW R&D follows stringent design guidelines where the 3D machine models not only go through the static analysis but also prove out in frequency-based dynamic analysis (Fig 1). Moreover, BFW could be one of the first in machine tool industries where machine performance gets predicted at its design stage during design analysis based on digital twin technology.

R&D exclusively uses the python-based algorithm where the tool-tip dynamics result in the Frequency Response Function (FRF), which further leads to the prediction of the cutting performance of the machine even before building its physical prototype. Thus, the 3D machine model dynamics, tooltip FRF, and stability lobe diagram (SLD) help predict the accurate dynamic performance of the machine at the design phase in the development of machining centres.


A disruptive ‘optimum stiffness-to-weight ratio’ based iCTech composite technology has been developed in-house to address present challenges faced while using existing cast iron and steel fabricated machine structures (Fig 2).

The iCTech enhances the existing static and dynamic properties of machine structures in many ways, thanks to its unique mixture formula. A comparison of an iCTech machine with an existing one has shown significantly improved stiffness and damping characteristics for machine tool structures that stand out in the crowd.

BFW R&D has developed a glass fibre reinforced epoxy granite (GFEG) vertical milling centre with an academic collaborator, PSG College of Technology, Coimbatore (Fig 3). The project has been successfully accomplished with India’s first indigenously developed GFEG machine with the major funding from PSA office Govt. of India. This GFEG machine structure delivers at least a 100% improvement in productivity in terms of MRR along with higher product surface quality. BFW is looking forward to implementing this technology in the upcoming products where precision and superior part finish are the major objectives.

The machine-dynamics-based performance tool has been recently developed and is in the testing phase. This performance tool predicts the cutting performance of a typical machine even at the design phase (Fig 4). This stability lobe diagram (SLD)-based technology offers the luxury to redesign or modify the existing line of machines, considering the specific customer demands with respect to the performance of the machine. This performance tool is developed around all the necessary inputs, such as cutting tool geometry, workpiece material, processing parameters, and the dynamics of a machine, making the machine performance predictions closer to reality.

A novel intelligent real-time thermal control module (iRTC) will be a game changer while addressing all the thermal issues in the machines in the coming days. The iRTC module intelligently addresses the effects of the environment, spindle running, and spindle cooling during the cutting operation. The iRTC module is based on the physics of heat generation, and the compensation strategy is based on the partial difference method. The iRTC module is developed both for the spindle and the machine structure in order to improve the effectiveness of spindle cooling (in case of motorised spindle) and has been compared with the standard chiller control system. The iRTC module improves the part precision up to 90%. Therefore, the upcoming BFW machining centers can be expected to take care of thermal issues achieving the required part precision with the help of an optional real-time based iRTC module.


Finally, towards sustainable growth, foundry waste sand from BFW’s Hosur-based foundry plant is innovatively transformed into lightweight construction bricks and the raw material for 3D concrete printing. The Hosur plant annually produces around 400 tonnes of foundry waste sand, which is challenging for its disposal in the environment.

However, BFW’s R&D team has introduced a unique transformation methodology where the waste sand is 100% used for the manufacturing of lightweight construction bricks after post-treatment. The commercialisation of the waste sand bricks is planned for this year, and an annual income is expected from the same.

BFW believes that R&D has positively invested throughout the tough period of the pandemic during the years 2020–21, and it expects some ground-breaking technologies and features in the product line to improve customer service in the upcoming years.

Image Gallery

  • Fig 1 - Finite element based dynamic analysis of the machining centre

    Fig 1 - Finite element based dynamic analysis of the machining centre

  • Fig 2 - A cross-sectional view of the iCTech composite technology enabled machine

    Fig 2 - A cross-sectional view of the iCTech composite technology enabled machine

  • Fig 3 - GFEG made vertical milling centre

    Fig 3 - GFEG made vertical milling centre

  • Fig 4 - Validation of stability lobe diagram (SLD) based machine performance optimisation

    Fig 4 - Validation of stability lobe diagram (SLD) based machine performance optimisation

  • Dr Harshad Sonawane
Head- Research and Development activities
Dr Kalam Centre, Innovation
Bharat Fritz Werner (BFW)

    Dr Harshad Sonawane

    Head- Research and Development activities

    Dr Kalam Centre, Innovation

    Bharat Fritz Werner (BFW)

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