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Drill Resharpening tips & techniques: 💡.

Drill Resharpening tips & techniques: 💡.

Getting ahead in the infinite game; the game of constant improvement.✴️. 📈.

As we live out our core purpose on a daily basis everyday at work, we realize we are not solely about winning more business and customers orders;

but we are about helping our our team teach and our customers learn how to use technology better.

Yean Lu Yl is about improving customers productivity to increase our customers manufacturing profitability on a daily basis. ↗️.

As part of this endeavor, apart than simply winning our customers orders and delighting them with our after sales services, we have now started assisting companies struggling with getting technical services, spares, training, alignment & reconditioning services for their existing range of drill and end mill Resharpening machines.

Stuck with your Drill Regrinding machine and not getting appropriate answers to your querries & tech support ?

We shall be happy to help ✅.

Drop details of difficulties faced on your machine on our WhatsApp number : +91.7698968689 to fast track your machines return as a value adding asset 👨‍🔧.

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Success Case Story

Combicham

Combicham

Application: Drilling Through Hole
Material: Group 10 – High alloyed steel, cast steel and tool steel
Industry: Job-shop
Machine: Milling Machine – Vertical 12KW
Coolant: Emulsion / Internal 20 BAR
The Target: Increase productivity

Competitor

ISCAR

Drill

SD524-26-104-32R7​

MNC 260-130 A32-150-06-5D​

Insert

SPGX0903-MC​

SOGX 060304-W ICP150​

Insert Grade

DS4050​

IC808/908​

Tool/Insert Material

Carbide Coated​

Carbide Coated​

Hole Diameter (mm)

26​

26​

Hole Depth (mm)

90​

90​

Cutting Speed (m/min)

110​

130​

Spindle Speed (rpm)

1347​

1592​

Feed (mm/rev)

0.1​

0.17​

Table Feed (mm/min)

135​

271​

Holes per Cutting Edge for a new Corner

48​

120​

Primary Wear

Flank Wear​

Flank Wear​

Surface Quality

Bad​

Good​

Chip Type

Tight​

Tight​

Metal Removal Rate  (cm3/min) 

71.5​

143.65​

Test Results:

With the COMBICHAM, we were able to significantly reduce the machining time on a machine with low power.​

Tool is running smother than competitor’s tool and delivers a better surface quality .

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Success Case Story

Emuge 16 mm Endmill used at Hicon Technocast

Emuge 16 mm Endmill used at Hicon Technocast

Success Story of Our Emuge Endmill 16 mm used in Component : Connection Plate  at Hicon Technocast – Metoda in material SS 304 –against Shining & Blood.

Objective of Trial was Increase life of components

Please find the below trial details and attached TQ of complete application details :-

  • EFI20001.016 – 16 mm Top Cut Endmill
  • Finishing  – Face Milling Operation, OD and ID
  • Component – Connection Plate
  • 2000 RPM
  • 350 Feed
  • Ap – 0.1
  • Ae – 16 mm
  • Depth of cut – Used for finishing operation to remove 0.1 mm Stock Blood Competitor
  • 20-22 piece Shining Competitor – 15-17 piece
  • Cycle time – 11 min
  • Milling Cycle Time
  • 1.5 Hour for whole job
  • Hass VMC VF2
  • Current contact time life of 3+ Hours

Our Life – 45+ Components with very good finishing

View Additional Details

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Success Case Story

Success Story of Our Witmans Oil used at Hicon Technocast – Metoda (Used in material Cast Stanless Steel) against Quaker Oil.

Success Story of Our Witmans Oil used at Hicon Technocast – Metoda (Used in material Cast Stanless Steel) against Quaker Oil.

Objective of Trial was CPC Production.

Hicon Technocast got below benefits:

  • Reduce Oil Consumption by almost 30%
  • Improve Tool Life by almost 50% In Drilling , Deep Hole Drilling and Boring

Categories
Success Case Story

Cosmos – Digifac (our principal for IIOT Product machine monitoring system) at customer Precision Manufacturing company.

Cosmos – Digifac (our principal for IIOT Product machine monitoring system) at customer Precision Manufacturing company.

In this below improvements done.

  • identifying real downtime and reduction
  • improving in productivity (optimum utilization of the machines)
  • optimum programing
  • minimize the gap (operation time and cutting time, minimize air time in programs) etc.

Know More

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Success Case Story

Heat Exchanger-ISCAR Sumo Cham Drill-Stacked Plate

Heat Exchanger-ISCAR Sumo Cham Drill-Stacked Plate

D32.5 stacked plate drilling test report.
Our Sumocham works best in stacked plate drilling.

RESULT

  • Tool life increased 25% Min
  • Better quality & small chips
  • Smooth cut

Know More

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IIoT OEE

How manufacturers can improve OEE using IoT

Optimized-How-Manufacturers-can-Improve-OEE-using-IoT-1-850x580

How manufacturers can improve OEE using IoT

Today, the Manufacturing Industry faces stiff global competition due to new companies and new brands entering the market each day. Factors such as quality, efficiency, and deliverability are now the benchmarks for a company’s success. Optimizing Overall Equipment Efficiency (OEE) to maintain manufacturing productivity standards is crucial as it directly impacts business performance. Let’s explore what OEE is and how IoT can provide visibility to manufacturing companies to understand production losses and improve overall OEE.

What is OEE?

Overall Equipment Effectiveness or OEE is a standard to measure the manufacturing productivity across industries. Manufacturers are continually striving to achieve 100% OEE, but many reasons can affect productivity.

You can improve profitability by optimizing your processes in various ways. Still, it can be challenging to understand the overall effectiveness of a complex operation that includes multiple pieces of equipment and where each machine’s effectiveness is co-dependent.

OEE is one metric that will help you to meet this challenge. OEE helps manufacturers access the process’s reliability and health and check if it works at the required accuracy level. Manufacturers can identify gaps in machine utilization and resource utilization and compare them with the quality and availability of the finished product.

OEE is calculated by multiplying the three main factors:

  1. Availability
  2. Productivity
  3. Quality
calculate OEE

To reduce OEE losses, proper availability of machines, and maintenance and handling of equipment are vital. To find the root cause and rectify errors, manufacturers can effectively use a powerful tool like IOT to accurately and consistently monitor existing bottlenecks. IoT provides data that helps manufacturers to find the inconsistencies in their process. 

Six Big Losses of OEE (Overall Equipment Effectiveness)

Seiichi Nakajima is the father of OEE and TPM (Total Productive Maintenance), and he first used OEE to measure and track production performance. He created a 6-point framework called “Six Big Losses” to capture the inefficiencies. The six big losses are connected to the three main factors of OEE, which are described above.

Here are the Six Big Losses of OEE

Six Big Losses OEE

Availability Losses

Unplanned Downtime 

Unplanned Downtime is a significant amount of time when the equipment scheduled for production stops working because of equipment failure. It can also happen because of material shortages, part breakdown, or unplanned maintenance. Unplanned downtime or equipment failure is the leading cause of expenses for manufacturers.

Predictive maintenance using IoT can help manufacturers to tackle unplanned Downtime. IoT can help to gather data on temperature, machine vibrations, and current. Manufacturers can analyze the data collected through IoT devices to narrow down and pinpoint the symptoms preceding any old failures. This data helps manufacturers to predict when machine breakdowns can happen in the future and service the equipment before a failure. Predictive maintenance using IoT helps to reduce not only production downtime but also the meantime to repair.

Planned Downtime

Planned Downtime is a significant amount of time when the equipment scheduled for production is not operating due to part changes, tool adjustment, or planned maintenance and inspection. Even though planned Downtime is unavoidable, IoT can help manufacturers reduce the impact.

Unlike scheduled maintenance based on a periodic schedule, Predictive maintenance is performed based on the equipment’s condition and helps reduce availability losses and Planned Downtime.

The IoT data provides insights into Planned Downtime events and gives manufacturers the visibility to see inefficiencies in processes during part changes and tool changes. This visibility helps manufacturers take corrective action to reduce these inefficiencies.

Performance Losses

Reduced Speed

Reduced speed is when the equipment runs slower than the ideal cycle-time, directly affecting the total production output. 

Worn out or dirty equipment, poor environmental conditions such as high levels of humidity or dust, insufficient lubrication, substandard materials, and operator inexperience can be some of the reasons for reduced speed. 

IoT sensors can provide manufacturers with vibration data enabling operators to know when the machines are not running at reduced speeds. In addition to the vibration data, environmental sensors can provide information on the environmental factors that affect the speed and help manufacturers learn the underlying reasons and to take remedial action.

Minor Stops

Minor stops, idling, shortstops are when equipment stops operating for a short time, like a minute or two. Usually, this happens due to material jams, misfeeds, misaligned parts, quick cleaning, or incorrect settings. Since these stops are for a short duration, manufacturers usually ignore them and are blind to their impact. In the long run, these minor stops can have a snowball effect and affect OEE.

IoT sensors can provide manufacturers insights into the frequency and reasons for minor stops. The data gives manufacturers clarity on the exact place these short stops occur in the production process, helping them understand chronic problems and resolving them.

Quality Losses

Process Defects

Process Defects occur when products are not manufactured as per the established quality standards even during the stable or steady-state production resulting in either rework or scrapped products. Process defects happen due to operator or machine handling errors, incorrect equipment settings, or the inconsistency in raw material quality due to the factory’s environmental conditions. 

The data gathered through IoT sensors help manufacturers monitor the equipment, determine reasons for process defects and detect environmental anomalies affecting raw material quality.

Start-up Losses

Start-up losses occur when defective parts are produced from the start-up until a steady production state is reached. The faulty parts include parts that need rework and parts that need to be scrapped. Start-up losses occur in machines that need warm upcycles or incorrect settings when a new part is run.

The data harnessed from IoT devices can provide manufacturers an indication as to which start-up conditions or changeover cycle creates more defects. Manufacturers can leverage this data to make decisions to tackle these issues.

Final Thoughts

IoT enables manufacturers to identify and rectify factors that negatively impact OEE. Monitoring equipment performance, reducing downtimes, and process defects using analytics produced by connected devices help manufacturers make informed decisions and proactive steps to limit production losses.

Manufacturers can obtain a wealth of production data and operational specifications by implementing IoT solutions and sensors connected to their existing Controller or PLC systems. Using a machine monitoring system like IoT will provide manufacturers with valuable data for future analysis.

Categories
IIoT

Challenges and Benefits of Industrial IoT implementation

Challenges and Benefits of Industrial IoT implementation

Digitizing your factory is taking your first step towards Industry 4.0 using the Industrial Internet of Things (IIoT). IIoT is no longer just a catchword but is being used by factories and machine shops worldwide. More and more manufacturing companies are adopting Industrial IoT and getting a competitive advantage by driving great results.

In this article, we will discuss the challenges and benefits of Industrial IoT implementation.

What is the Industrial IoT?

Industrial IoT (IIoT) is a seamless interaction between people, machines, processes, and information technology. IIoT uses manufacturing data, analytics, and cloud computing to help companies improve their operations, increase productivity, and improve quality. Industries use the Internet of Things (IoT) for applications such as remote monitoring and predictive analytics of their factory. Industrial IoT allows them to monitor the factory remotely from anywhere.

IIoT is a vital part of the Industry 4.0 industrial revolution and plays a significant role in creating manufacturing excellence and helping in the digital transformation of factories. The primary issue manufacturers face today is the lack of transparency and visibility of factory performance due to the unavailability of IT (Information Technology) and OT (Operational Technology). IT is for gathering information or data, and OT manages the physical operations and machines that carry out the manufacturing processes. 

Digital transformation is about adopting new technology for rapid growth and the rapidly evolving business models fuelled by this technology. Data-driven manufacturing provides manufacturers with a competitive edge to prosper in an exceedingly competitive landscape.

Challenges faced by manufacturers

Manufacturing companies that implement IIoT solutions for their factories are trying to manage their operations efficiently. One of the problematic tasks manufacturing companies face is making a radical shift in following management practices. Measuring your production and performance parameters is the first step towards efficiency, but it now needs to be backed by data for which IIoT is the key.

Here are some of the top challenges faced by manufacturers like you while implementing IIoT:

Finding the right IIoT integrator

Regardless of the expensive or the new technology you have, it can become obsolete if you don’t have the right team to onboard it for your company. Industrial companies can successfully adopt IIoT if they have the right provider and an integrator who knows IIoT technology. The integrator should understand the integration requirements and have hands-on experience in the manufacturing sector. 

It is recommended to appoint an external integrator right from your IIoT integration to the implementation phase. This process will ensure that you get the results and ROI you want.

Suitable Hardware and Data Connectivity

Old equipment and legacy machines, and newer machines can be easily integrated with new technology and are compatible with cloud-based systems like IIoT. 

IIoT technology can extract data from machine sensors and controllers using cloud-based systems via the internet. This data helps manufacturing companies understand their productivity, machine downtime and improve efficiency.

Companies need to examine their existing hardware infrastructure and assess future needs when researching for IIoT solutions for their factory. Based on their goals, they can choose an IIoT solution compatible with their existing machines and keep an eye on their future needs to see that these solutions are scalable to your business needs.

Data Security

Data security is another challenge in adopting IIoT for your factory. A data breach can stop your work till you can restore backup systems. As cloud storage is becoming a norm, companies should work with an IIoT integrator who understands these challenges and secure their data by establishing protocols and safety measures to reduce the risk of security vulnerability.

Data processing Capacity

Companies need to analyze their data processing needs before they develop the IoT architecture for their factory. An experienced integrator will help companies assess their current data processing ability and how they can scale it up in the future.

Data Migration/Integration

Companies also need to check whether the server’s data can be easily migrated to their ERP systems.

Benefits of IIoT

Increased Machine Utilization

Machines connected through Industrial IoT give manufacturers real-time insight into the key performance indicators and machine health. The KPIs can include Overall Equipment Effectiveness and Overall Process Effectiveness, enabling manufacturers to manage unplanned downtime. Based on the data, companies can schedule preventive maintenance, thereby increasing machine utilization.

Predictive Maintenance

Machine downtime has a significant impact on productivity for a manufacturing company. When companies approach machine downtime in a reactive rather than a proactive manner, they spend a considerable amount of time trying to find out the issue, resolve it, what parts they need, and how much it will cost. 

IIoT allows continuous monitoring of machines and helps manufacturing companies use predictive maintenance to reduce machine downtime.

Reduce human error

A company using IIoT can digitize its entire supply chain and track inventory in any of its locations. By using Industrial IoT, companies can minimize manual labor and mitigate the risk of human error. 

Increased safety at the workplace

Companies that are adopting IIoT solutions in their factory are helping make their factory a safer place to work. Interconnected IIoT devices that monitor safe machine operating parameters such as pressure, vibration, gas leaks and the heat produced during manufacturing processes can help avoid accidents by alerting the factory floor workers.

Increased operational efficiency

Machines connected to software through adding sensors send a steady stream of data about their performance. This connectivity helps manufacturers get a more in-depth insight into the working of each machine. 

IIoT enables manufacturers to make decisions that are data-driven and reduce bottlenecks in the production process. Companies can increase operational efficiency when they can amend processes in real-time, helping them reduce operating costs.

Factors that influence successful IIoT implementation

Independent data audit team

The first step to a successful implementation of Industrial IoT in your factory is to set up a digitalization department or a data audit department. The department will be responsible for conducting regular data audits for the successful implementation of IoT.

Open communication between team members

The success of any IIoT implementation is open communication between team members of different departments. Efficient collaboration between production, maintenance, supply chain, and other verticals will bolster the implementation process and impact the IIoT implementation’s effectiveness.

Reliable and experienced IIoT integrator

It is vital to choose the right technology provider and integration partner to implement IIoT infrastructure in your factory. An automation partner who has the skill and knowledge of working with manufacturing companies will be the right choice for your industrial company. The right integrator will help you leverage the gathered operational data to add value to your business outcomes.

IIoT infrastructure

A reliable WIFI network or LAN network (Good internet connectivity on shop-floor) and a  dedicated screen if there is a need to monitor the data continuously.

Setting Key Performance Indicators

Selection and tracking of Important Key Performance Indicators, which affects the whole manufacturing process and performance. KPI’s are measurable values that indicate the 

According to the application, KPI varies as per the selected machine like CNC, Press, Furnace, Energy meters, etc.

Challenges and Benefits of Industrial IOT

To conclude, manufacturing companies all across the world are extensively using IIoT in their factories. IIoT helps them to maintain machine uptime, reduce waste, increase revenue, and decrease costs. With the help of IIoT, manufacturing companies can do demand forecasting, enhance product quality and get products to market faster.