Building a ₹26,000 Cr. company after 36 rejections!
This is the story of Amrit Acharya who left a cushy McKinsey & Company job in the US in 2018 to fix India’s broken manufacturing supply chain.
The problem?
Manufacturing wasn’t "hot." Too complex and capital-heavy.
Investors didn’t bite, 36 turned him down.
But Amrit saw the gap; small manufacturers needed scale, and big companies needed reliable suppliers. He built ZETWERK to bridge the two.
What happened next?
2019: 500+ suppliers, ₹64 CR funding (Accel, Sequoia)
2020: ₹321 CR revenue, COVID hit but Zetwerk scaled when others paused
2021: ₹835 CR revenue, unicorn status
2022: ₹4,961 CR revenue, ₹21,000 CR valuation
Today: ₹14,596 CR revenue, 10,000+ suppliers, 9M+ manufactured parts
Zetwerk didn’t just scale, it changed Indian manufacturing.
It cut inefficiencies, reduced import dependence, and proved that India could build industrial giants, not just IT unicorns.
It was a problem that we didn’t know we had.
The lesson?
The biggest opportunities are where no one’s looking.
📠How process engineers optimise a grinding circuit:
The optimization process typically includes the following steps:
1. Data Collection and Analysis:
🔹 Conduct detailed tests to understand the ore's physical and chemical properties, including hardness, grindability, and mineral composition.
🔹 Gather historical and real-time data on circuit performance, including throughput, particle size distribution, energy consumption, and wear rates.
2. Circuit Design Review:
🔹 Flow Sheet Analysis: Review the current circuit design, including the configuration of mills, classifiers, and ancillary equipment.
🔹 Identify any bottlenecks or inefficiencies in the current design.
3. Grinding Media Optimization:
🔹Optimize the size, type, and material of grinding media to improve grinding efficiency and reduce wear.
🔹Ensure optimal media loading to balance energy consumption and grinding efficiency.
4. Mill Operation Optimization:
🔹Adjust mill speed and feed rate to optimize grinding efficiency.
🔹Optimize pulp density to improve grinding performance and reduce energy consumption.
🔹Use appropriate liner designs to enhance grinding efficiency and prolong liner life.
5. Classification Efficiency:
🔹Improve the performance of classifiers (hydrocyclones, screens etc.) to ensure proper separation of fine and coarse particles.
🔹Adjust the cut size to achieve the desired product size distribution.
6. Advanced Control Systems:
🔹Implement advanced process control systems (e.g., model predictive control) to stabilize the circuit and optimize performance.
🔹Use real-time monitoring and data analytics to make informed adjustments and respond to changes in ore properties and operating conditions.
7. Energy Management:
🔹Optimize mill power draw and operating conditions to minimize energy consumption.
🔹Evaluate the potential for energy recovery systems to improve overall energy efficiency.
8. Water Management:
🔹Optimize water usage to achieve the desired slurry density and flow characteristics.
🔹Implement water recycling systems to reduce fresh water consumption and improve sustainability.
9. Maintenance and Reliability:
🔹Develop and implement predictive maintenance schedules to minimize unplanned downtime.
🔹Use condition monitoring technologies to detect early signs of equipment wear and potential failures.
10. Operator Training and Engagement:
🔹Provide ongoing training for operators and maintenance staff on best practices and new technologies.
🔹Engage and incentivize operators to optimize circuit performance and contribute to continuous improvement.
11. Continuous Improvement:
🔹Conduct regular performance audits and reviews.
🔹Benchmark the circuit's performance against industry standards and best practices.
12. Integration with Upstream and Downstream Processes:
#Grainding_circuit_optimization, #Mill_Operation, #Process_Optimization, #Grainding_Media#Ball_Mill, #SAG_Mill,
Why P80 Matters: The Science of Grinding Circuit Efficiency
In mineral processing, few metrics are as fundamental—and as misunderstood—as P80. This parameter, which defines the particle size at which 80% of the material passes, is not just a quality control number; it is the core of grinding circuit performance and a powerful driver of downstream recovery in flotation, leaching, and overall plant efficiency.
🎯 Why P80 is Critical:
Achieving the correct grind size directly influences mineral liberation. If P80 is too coarse, valuable minerals remain locked in gangue, reducing recovery. If it's too fine, overgrinding occurs—leading to increased energy consumption, excessive slimes, and higher reagent usage in flotation and leaching circuits.
âš™ï¸ Hydrocyclone and Mill Performance:
Maintaining a consistent P80 requires tight control over the hydrocyclone classification system. Fluctuations in cyclone feed pressure, incorrect vortex/apex sizes, or misaligned slurry density can result in significant shifts in cut size, leading to either recirculation overload or product inefficiency.
Meanwhile, mill efficiency—both in SAG and ball mills—is directly tied to grind energy input vs. liberation output. Excess residence time or high circulating loads often result in a diminishing return on energy invested. It’s not about grinding more—it’s about grinding smarter.
🔄 The Domino Effect on Downstream Processes:
A well-controlled P80 improves flotation selectivity, ensuring better bubble-particle attachment, reducing entrainment of fine gangue, and lowering collector/frother dosages. In leaching, optimal P80 maximizes surface area without compromising permeability, enhancing metal dissolution kinetics while maintaining filterability and leach pad stability.
✅ Plant-Wide Benefits of P80 Optimization:
Reduced energy consumption per tonne
Stabilized reagent usage
Enhanced recovery and concentrate grade
Improved tailings dewatering and environmental compliance
Lower operational costs across the board
🔠If you're not actively monitoring and optimizing your plant's P80, you're leaving recovery—and profit—on the table.
Let’s talk: How are you optimizing P80 in your grinding circuit? What control strategies, instrumentation, or simulation tools are you using?
#GrindingOptimization#P80#MineralProcessing#HydrocycloneControl#MillEfficiency#ProcessControl#Comminution#FlotationPerformance#LeachingKinetics#MetallurgicalRecovery#MiningInnovation#MineralLiberation#MiningLeadership#ProcessingPlantExcellence
I believe AI creates real value when it tackles hard, physical problems — the kind that live in factories, warehouses, and service tasks.
Recently, I learned the attached from a plastics machine manufacturer and logistics provider struggling with unpredictable production schedules, warehouse congestion, and reactive maintenance routines.
When a structured AI implementation approach was brought into the equation the following outcome was achieved 👇
🔹 Smart Production Planning – Machine learning models forecasted demand and optimized resin batch production, cutting material waste by 18%.
🔹 AI-Driven Warehouse Logistics – Intelligent slotting and routing algorithms boosted order fulfillment rates by 25%, reducing forklift travel time and idle inventory.
🔹 Predictive Maintenance for Service Teams – Sensor data and pattern recognition flagged early signs of machine wear, reducing unplanned downtime by 30%.
The result wasn’t automation replacing people — it was augmentation empowering people. Operators, warehouse managers, and service engineers gained real-time insights to make faster, better decisions.
💡 Takeaway: AI success in industrial environments isn’t about technology first — it’s about aligning data, people, and process to create measurable operational impact.
#AI#IndustrialServices#SmartManufacturing#WarehouseOptimization#PredictiveMaintenance#DigitalTransformation#OperationalExcellence
What connects Industrial IoT, Application and Data Integration, and Process Intelligence?
During my time at Software AG, my attention has shifted in line with the company's strategic priorities and the changing needs of the market. My focus on Industrial IoT, moved into Application and Data Integration, and now I specialise on Business Process Management and Process Intelligence through ARIS.
While these areas may appear to address different challenges, a common thread runs through them. Take a typical production process as an example. From raw material intake to finished goods delivery, there are countless interdependencies, processes and workflows, and just as many data sources.
Industrial IoT plays a key role by capturing real-time data from machines and sensors on the shop floor. This data provides visibility into equipment performance, production rates, energy usage, and more. It enables predictive maintenance, reduces downtime, and supports continuous improvement through real-time monitoring and analytics.
Application and Data Integration brings together data from across the value chain, including sensor data, manufacturing execution systems, ERP platforms, quality management systems, logistics, and supply chain management. Synchronising these systems with integration creates a unified, reliable view of production operations. This cohesion is essential for automation, traceability, quality management and responsive decision-making across departments and geographies.
Process Management, including modelling, and governance, risk, and controls, takes a different yet equally critical perspective. Modelling helps design optimal process flows, while governance frameworks ensure controls are in place to manage quality, risk, and enforce conformance for standardisation.
Process mining uncovers bottlenecks, rework loops, and compliance deviations. It focuses on how the production process actually runs, rather than how it was designed to operate.
Despite their different vantage points, each of these domains works toward the same goal: aggregating, normalising, and structuring data to transform it into information that can be easily consumed to create meaningful, actionable insights.
If your organisation is capturing process-related data through isolated tools, such as diagramming or collaboration platforms, quality management systems, risk registers, or role-based work instructions, it is likely you are only seeing part of the picture.
Without a unified approach to integrating and analysing this data, the deeper insights remain fragmented or out of reach. By aligning physical operations, applications & systems, and business processes, organisations can move beyond surface-level visibility to uncover the root causes of inefficiency, unlock hidden potential, and govern change with clarity and confidence.
#Process#Intelligence#OperationalExcellence#QualityManagement#Risk#Compliance
100K+ Followers I TPM l 5S l Quality l VSM l Kaizen l OEE and 16 Losses l 7 QC Tools l COQ l SMED l Policy Deployment (KBI-KMI-KPI-KAI), Macro Dashboards,
Finding the Right Balance in Cement Mill Operations: Circulation Factor vs. Reject Rate
Imagine you're standing in front of a cement mill, its hum a constant reminder of the delicate balance between energy efficiency and cement quality. Behind the scenes, two key factors—circulation factor and reject rate—are shaping your operations. Getting them right can transform your mill’s performance.
So, how do you find the sweet spot?
1. Circulation Factor: The Key to Efficiency
The circulation factor reflects how much material stays inside the mill versus how much exits. A high factor means more grinding time, improving quality—but at the cost of higher energy use and wear on the equipment. Too low, and the material isn’t ground enough, resulting in poor-quality cement.
What you can do:
Monitor material flow: Excessive recirculation wastes energy.
Adjust mill speed: Slowing it down can reduce energy consumption.
Use the right grinding media: A good mix of ball sizes optimizes grinding.
2. Reject Rate: The Hidden Cost
The reject rate tells you how much material doesn't meet quality standards and must be discarded or reprocessed. High reject rates often indicate problems with raw materials, grinding, or classification.
What you can do:
Ensure raw material quality: Consistent quality leads to better cement.
Optimize classifier settings: Fine-tune to improve separation and reduce rejects.
Balance mill load: An overloaded or underloaded mill increases rejects.
3. Real-Time Adjustments: Stay Agile
Adjusting the circulation factor and reject rate isn’t a one-time task. Continuous, real-time adjustments are necessary to keep the mill running at its best.
What you can do:
Use sensors and monitoring systems: Track everything from material flow to temperature for quick adjustments.
Automate settings: Real-time automation of mill speed, load, and classifier settings reduces errors.
4. Energy Efficiency: Small Changes, Big Impact
Both factors influence energy consumption. A high circulation factor leads to excessive grinding, while a high reject rate forces more regrinding—both increase energy usage.
What you can do:
Find the right balance: Optimize circulation factor and reduce reject rates to minimize energy waste.
Maintain equipment: Well-maintained machines use less energy.
5. Continuous Improvement: Never Stop Refining
Optimizing these factors is an ongoing effort. Equipment wear, changing raw materials, and evolving conditions mean you need to keep monitoring and adjusting.
What you can do:
Monitor regularly: Keep track of mill performance and adjust quickly.
Train operators: Empower your team to make informed adjustments.
Adopt new technology: Stay updated on tools that improve performance and reduce energy consumption.
finally, how do you manage these factors in your cement mill? What challenges have you faced?
#CementProduction#MillOptimization#EnergyEfficiency#SustainableManufacturing#CementQuality#ProcessImprovement
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Sales & Operations Planning (S&OP) is a structured, cross-functional process that aligns demand and supply to drive business performance. It brings together sales, marketing, finance, and operations to create a single, unified plan that balances customer demand with supply chain capabilities. A well-executed S&OP process enhances decision-making, improves service levels, optimizes inventory, and drives profitability.
Here’s a structured S&OP process flow:
ðŸ. ð——ð—®ð˜ð—® ð—šð—®ð˜ð—µð—²ð—¿ð—¶ð—»ð—´ & ð—”ð—»ð—®ð—¹ð˜†ð˜€ð—¶ð˜€
> Collect historical sales, promotions, and external market data.
> Use statistical methods to uncover trends and demand drivers.
> Assess supply chain capabilities, constraints, and lead times.
ðŸ®. ð——ð—²ð—ºð—®ð—»ð—± ð—£ð—¹ð—®ð—»ð—»ð—¶ð—»ð—´
> Analyze historical trends and market forecasts.
> Develop a demand plan aligned with strategic business goals.
> Incorporate inputs from sales, marketing, and finance to refine accuracy.
ðŸ¯. ð—¦ð˜‚ð—½ð—½ð—¹ð˜† ð—£ð—¹ð—®ð—»ð—»ð—¶ð—»ð—´
> Formulate a supply plan covering production, inventory, and distribution.
> Factor in supplier lead times, capacity constraints, and inventory policies.
> Ensure supply is balanced with demand to optimize costs and service levels.
4. ð—–ð—¼ð—»ð˜€ð—²ð—»ð˜€ð˜‚𘀠ð—¥ð—²ð˜ƒð—¶ð—²ð˜„
> Bring demand and supply plans together for cross-functional evaluation.
> Identify gaps, constraints, or mismatches in plans.
> Collaborate to develop an optimized and executable plan.
ðŸ±. ð—˜ð˜…ð—²ð—°ð˜‚ð˜ð—¶ð˜ƒð—² ð—¥ð—²ð˜ƒð—¶ð—²ð˜„
> Present the integrated S&OP plan to senior leadership.
> Incorporate feedback and finalize decisions.
> Ensure alignment with long-term strategic goals and financial objectives.
A well-structured S&OP process drives efficiency, profitability, and resilience in supply chain operations.
#SupplyChain#SOP#DemandPlanning#SupplyPlanning#OperationsManagement#BusinessStrategy#Forecasting#InventoryManagement#SupplyChain#Analytics#SafetyStock#CostOptimization#Logistics#Procurement#InventoryControl#LeanSixSigma#Cost#OperationalExcellence#BusinessExcellence#ContinuousImprovement#ProcessExcellence#Lean#OperationsManagement
15M+ | Helping Consultant to think beyond T-codes | SAP EAM Architect | Problem Solver and Continuous Learner | SAP-Mentor | Changing Lives by making SAP easy to Learn |
IVL | EX-TCS | EX-IBM |
End-to-End Process in a Manufacturing Plant Using SAP Modules ðŸŒ
In a manufacturing plant, numerous processes come together to create a seamless production flow.
SAP integrates all these processes to ensure that every step
—from planning to execution—is optimized.
1. ð——ð—²ð—ºð—®ð—»ð—± ð—£ð—¹ð—®ð—»ð—»ð—¶ð—»ð—´ (ð—¦ð—”ð—£ ð—£ð—£ - ð—£ð—¿ð—¼ð—±ð˜‚ð—°ð˜ð—¶ð—¼ð—» ð—£ð—¹ð—®ð—»ð—»ð—¶ð—»ð—´)
It all begins with forecasting demand for the finished product.
In SAP PP (Production Planning), demand planning helps predict how much product is needed in the future.
💡 Example: A company that manufactures cars uses Material Requirements Planning (MRP) to forecast the number of vehicles they need to produce in the next quarter.
T-Code: ð— ð——ðŸ²ðŸ (Create Planned Independent Requirements)
ðŸ®. ð—£ð—¿ð—¼ð—°ð˜‚ð—¿ð—²ð—ºð—²ð—»ð˜ (ð—¦ð—”ð—£ ð— ð— - ð— ð—®ð˜ð—²ð—¿ð—¶ð—®ð—¹ð˜€ ð— ð—®ð—»ð—®ð—´ð—²ð—ºð—²ð—»ð˜)
Once the production demand is clear, the materials required for manufacturing need to be procured.
This is where SAP MM comes into play. Purchase requisitions are created, and purchase orders are sent to vendors.
💡 Example: To produce a car, materials like steel, engine parts, and tires need to be ordered from suppliers.
T-Code: ð— ð—˜ðŸ®ðŸð—¡Â (Create Purchase Order)
ðŸ¯. ð—£ð—¿ð—¼ð—±ð˜‚ð—°ð˜ð—¶ð—¼ð—» ð—˜ð˜…ð—²ð—°ð˜‚ð˜ð—¶ð—¼ð—» (ð—¦ð—”ð—£ ð—£ð—£)
After procurement, the actual production process begins in the plant.
SAP PP handles the creation of production orders, scheduling, and tracking of the production process.
💡 Example: The car production process is broken down into operations like body assembly, engine installation, and painting. SAP PP ensures that every operation is planned and executed in sequence.
T-Code: CO01 (Create Production Order)
ðŸ°. ð—¤ð˜‚ð—®ð—¹ð—¶ð˜ð˜† ð— ð—®ð—»ð—®ð—´ð—²ð—ºð—²ð—»ð˜ (ð—¦ð—”ð—£ ð—¤ð— )
As products are manufactured, they undergo quality inspections. SAP QM ensures that each product meets quality standards before moving forward.
💡 Example: In the car manufacturing process, after engine installation, a quality check is performed to ensure it’s functioning correctly. This is recorded in SAP QM.
T-Code: QA32 (Results Recording for Inspection Lot)
ðŸ±. ð— ð—®ð—¶ð—»ð˜ð—²ð—»ð—®ð—»ð—°ð—² (ð—¦ð—”ð—£ ð—£ð— - ð—£ð—¹ð—®ð—»ð˜ ð— ð—®ð—¶ð—»ð˜ð—²ð—»ð—®ð—»ð—°ð—²)
To keep the machinery running smoothly, regular maintenance is critical. SAP PM (Plant Maintenance) manages preventive and corrective maintenance to avoid downtime in the production line.
💡 Example: A conveyor belt in the plant needs regular lubrication. SAP PM schedules this preventive maintenance, ensuring that the production line operates efficiently.
T-Code: IW31 (Create Maintenance Order)
ðŸ². ð—ªð—®ð—¿ð—²ð—µð—¼ð˜‚ð˜€ð—² ð—®ð—»ð—± ð—œð—»ð˜ƒð—²ð—»ð˜ð—¼ð—¿ð˜† ð— ð—®ð—»ð—®ð—´ð—²ð—ºð—²ð—»ð˜ (ð—¦ð—”ð—£ ð—ªð— /ð—˜ð—ªð— )
Once the finished products are ready, they are stored in the warehouse.
ðŸ³. ð—¦ð—®ð—¹ð—²ð˜€ ð—®ð—»ð—± ð——ð—¶ð˜€ð˜ð—¿ð—¶ð—¯ð˜‚ð˜ð—¶ð—¼ð—» (ð—¦ð—”ð—£ ð—¦ð——)
The final step is delivering the finished products to customers. SAP SD (Sales and Distribution) handles customer orders, shipping, and billing.
T-Code: VA01 (Create Sales Order)
#sap#process
From Constant Vibration to Stable Operations: Coal Mill Optimization.
A few months back, we were struggling with constant vibrations at one of our VRMs. The root cause pointed toward an unstable and insufficient bed layer. A thin or fluctuating layer doesn’t just create vibration — it also compromises efficiency, drying, and downstream flame stability.
We decided to address the problem systematically. Here are some of the practical adjustments we applied on shift that helped us stabilize the mill and achieve a decent improvement in bed thickness and overall performance:
✅ Increased fresh coal feed gradually — more feed naturally supports a thicker grinding bed.
Increase feed by small step (e.g., 1–5% of current feed). Wait 5–10 minutes for stabilization. Observe ΔP and motor current. If ΔP and motor current increase modestly and outlet temp stable → continue; if either approaches alarm, revert.
✅ Reduced separator speed slightly, allowing more coarse return to the grinding zone.
If more bed needed after feed step, reduce separator speed slightly (small rpm decrement). This returns more coarse material to the bed. saperator higher speeds is a good choice but it also increases the amount of return fines which will just make things worse (mill dusty/uneven bed). Watch product fineness and downstream LOI.
✅ Fine-tuned primary air/draft to increase material residence time while keeping transport stable.
Adjust mill fan draft / primary air — reduce PA or dampers slightly to increase residence time. Do this carefully: too low PA risks choking and poor transport to classifier. Watch flame/combustion and coal pipe distribution.
✅ Adjust grinding pressure carefully within hydraulic limits to hold the bed firmly.
✅ Trialed small water injection (within recommended limits) to stabilize the layer further.
for VRMs, small controlled liquid injection can increase bed stability and apparent layer thickness. (FLSmidth recommends incremental increases up to ~2% fresh feed as a trial).
✅ Inspected liners & retaining ring geometry — often overlooked, but wear can impact bed build-up. layer thickness Calibration, accumulor nitrogen pressure, water nozzles blockage, table and roller condition, saperator fins etc aswell
All adjustments were done step-by-step, always monitoring:
Mill ΔP (pressure drop),
Main motor current,
Outlet gas temperature,
Separator speed/classifier rejects,
Coal fineness & downstream flame indicators.
âš ï¸ The key learning? Layer control is a balance. Too thin = vibration & poor grind; too thick = overload, high power, and possible choking. Small, incremental changes with close monitoring gave us the best results.
#CementIndustry#ProcessEngineering#CoalMill#VRM#OperationsExcellence#CementPlant#Optimization#ProcessControl