Transportation Route Optimization

There is consensus we should double down on #energyefficiency measures. Not only is fuel savings better for the environment; it’s also better for one’s pocket.💵   With the International Maritime Organization’s updated 2050 and interim emissions reduction targets, and with #CII and EU ETS now applicable to shipping,🚢 the impetus to improve energy and fuel efficiencies is even stronger.   Did you know that the sector has seen an energy efficiency gain of 30%, yet its emissions has remained comparable to 2008 levels because trade volumes have increased comparably over the same period?📈   And meeting the 2030 interim goals will require energy efficiency gains of another 35%, in addition to 10% green fuels adoption.😳   This is driving Global Centre for Maritime Decarbonisation (GCMD)’s PAYS pilots, with which we hope to spur adoption of energy efficiency technologies (EETs) by addressing pain points in fuel savings uncertainty and misaligned incentives between the investor and beneficiary.   And while the team is working on these pilots, my students and I took a hard look at how CII impacts commercial and operational decisions.🧐   We used data published in a Harvard Business Review case study about CMA CGM’s China-Western US operations as a basis for our analyses, recognising that outcomes can vary significantly depending on the details of trade route, vessel type, access to and cost of fuel, etc.🛢️   We limited our analysis to operational options of (A) slow steaming, and (B) replacing fuel oil with a B30 biofuels blend.🌱   The denominator in the annual efficiency ratio (AER), which comprises the deadweight tonnage and distance traveled by the vessel, is invariant in this exercise.🌏   To first order, slow steaming impacts fuel consumption📉 and a fuel switch impacts the emissions factor in the numerator of AER.   The table shows that a 17% reduction in fuel consumption with slow steaming extends the vessel’s compliant operations to 2034 (D-rated vessels can operate for a 3-year grace period); a 24% reduction in emissions factor with fuel switch extends operations by another 3 years.   Things become more interesting with commercial considerations:   💰We estimated annualised CAPEX, fuel cost and non-fuel OPEX; fuel cost is the largest expense (varies from 60 to 75%, depending on scenarios). 💰Because fuel consumption is NOT linear with speed, a 15% speed reduction can translate to a fuel savings as high as 40% (from 20 to 17 knots), or more modestly here, 17% (from 16 to 13.5 knots).   💰To transport the same amount of cargo, slow steaming could require deploying additional vessels. We found the addition of one more vessel increases annual expenses by 15%.   💰Fuel switch yields a 24% improvement in AER at 50% increase in fuel costs.   What is your experience with CII estimations? How have they impacted your commercial and operational decisions?🫵   Share with us other nuances you’ve learned!   Together, we are stronger; together, we can💪🏻

Essential Thumb Rules for Power Plant Engineers- Feedwater Temperature Impact: For every 6°C increase in feedwater temperature, fuel consumption for the same steam generation is reduced by approximately 1%. This highlights the importance of efficient feedwater heating. Flue Gas Temperature Reduction: A reduction of 22°C in flue gas temperature can lead to a 1% increase in boiler efficiency. Effective heat recovery systems are crucial for achieving this. Excess Air Management: A 15% reduction in excess air can enhance boiler efficiency by around 1%. While a 20% excess air margin is acceptable, striving for 3% while monitoring CO levels (not exceeding 50 ppm) can yield significant benefits. Saturated Steam Calculation: For saturated steam, the temperature can be approximated using the formula: T = sqrt{sqrt{P \times 100}} + 1 For instance, at a steam drum pressure of 100 bar, the steam temperature would be approximately 317°C, which serves as the inlet to the superheater. Insulation Efficiency: Insulating steam lines and components can reduce heat loss and improve overall efficiency by up to 2% compared to poorly insulated systems. Proper insulation is a critical investment. Soot Blowing Regimen: Implementing a regular soot blowing regimen can enhance boiler efficiency by 1-2%, ensuring optimal heat transfer and reducing fouling. Turbine Exhaust Temperature: For every 10°C reduction in turbine exhaust temperature, steam turbine efficiency may increase by about 1%. Turbine Blade Maintenance: Regular maintenance and cleaning of turbine blades can improve turbine efficiency by up to 2%. Advanced Control Strategies: Implementing advanced control strategies and automation can improve overall plant efficiency by 1-3%. High-Efficiency Equipment: Upgrading to high-efficiency equipment and technologies can yield efficiency improvements of up to 5-10%. Fuel Additives: Utilizing fuel additives can boost boiler efficiency by up to 2%. Boiler Loading Efficiency: Although there is no direct correlation between boiler loading and efficiency, it’s observed that boiler efficiency remains at about 85% of its maximum when operating below 50% loading, with peak efficiency between 85% to 95%. Heat Rate Optimization: For every 1% reduction in heat rate, overall plant efficiency can improve considerably. Water Quality Management: Maintaining optimal water quality in the boiler can reduce scaling and corrosion, potentially improving efficiency by up to 2%. Regular Performance Testing: Conducting periodic performance testing can identify inefficiencies and areas for improvement, yielding efficiency gains of 1-3% Combustion Optimization: Fine-tuning combustion parameters can enhance efficiency by up to 2%. Waste Heat Recovery: Implementing waste heat recovery systems can improve overall plant efficiency by 5-15%. #PowerPlantEngineering #Efficiency #Sustainability #Innovation #EnergyManagement

ANA Boeing 787-8 being washed at night. Washing makes the planes not only look good but actually saves on fuel burn. 🔥 ⛽️ Washing aircraft exteriors has been proven to be an effective means of reducing drag and thus improving fuel efficiency. Since unwashed aircraft can experience an up to 0.1 percent increase in drag, according to some reports a decrease in fuel efficiency in unwashed planes can be expected. “The periodic washing of airplane exteriors also results in minimized metal corrosion and paint damage, aids in locating leaks and local damage and improves the aesthetics of the airplane,” according to Boeing . “ The question of how frequently to wash aircraft is one of the many management decisions on minimizing the total cost of asset maintenance. Washing an directly incurs costs while not washing an aircraft indirectly incurs costs from future corrosion damage. Reducing the period between washes may reduce the cost of corrosion damage but increases the cost of washing.” Industry experts now, more than ever, are relying on regular washing and cleaning and in some cases are beginning to require that aircrafts operated in harsh environments be rinsed with clear water immediately after use.

🚲🚆 THE FUTURE OF MULTIMODAL TRANSPORT — LESSONS FROM THE NETHERLANDS In most cities, people arrive at the train station by car. In the Netherlands? People also arrive at the bike station by train. This simple shift reveals a radically different mindset—one where mobility is not a car-vs-bike debate, but a seamless partnership between bikes, trains, and walkable cities. 🔄 The Dutch Model: Seamless. Sustainable. Smart. The Netherlands has built a system where every mode plays to its strengths: 🚴♂️ Bikes for short, flexible trips 🚆 Trains for fast, long-distance travel 🧠 Smart planning to stitch it all together This isn’t theory—it’s real. Every day. 📊 Mind-Blowing Stats That Prove It Works ✅ 50% of Dutch train passengers arrive by bike. Not car. Not taxi. Bike. That’s half the crowd cutting emissions and congestion. ✅ Utrecht Central Station = 33,000 bike parking spaces. Yes, thirty-three thousand. A bike garage that looks like a metro station. ✅ €510M invested annually in cycling infrastructure. Result? €19B in healthcare savings. That’s a 37x return. Transport design = public health strategy. 🌍 A Vision of Multimodal Abundance What if every city embraced this mindset? 🚚 E-bikes delivering packages through dense neighborhoods 🚶♀️ Pedestrian-first communities tied together with light rail 🚲 Train stations as bike hubs—not just parking lots 🚦 Traffic systems designed for health and time, not just cars Instead of asking “Which mode should dominate?” The Dutch ask: “How can all modes work together?” 💭 What If… What if our cities didn’t just move people around… But moved people better? What if bikes and trains weren’t alternatives— But the system itself? This isn’t just a Dutch story. It’s a global invitation. 💬 Would this model work in your city? What’s the biggest barrier you see to a multimodal future? 👇 Drop your thoughts below. ➕ Follow me if you're into transportation that works for people—not just machines. — #Transportation #Cycling #Infrastructure #SmartCities #Netherlands #UrbanPlanning #Mobility #Sustainability #Multimodal #FutureOfTransport #PublicHealth #CityDesign

Ultimate Cell Hydrogen making performance booster explained at the L Lynch Plant Hire & Haulage training ground. Recently, I met with Gareth Eeson, MD of Ultimate Cell Distributors UK, to find out how this little device is reducing fuel consumption and carbon emissions while lowering maintenance costs. Gareth: “It’s really small we always reference it to the size of a can of beans. But it’s modular, so we can scale it for larger machines, from one unit up to six, depending on engine size and fuel flow.” How does it work? Gareth: “Each unit is connected to the machine and wired into an onboard electric power source. It then combines a small amount of electricity with a high-grade potassium hydroxide electrolyte. “This enables efficient electrolysis that splits water into hydrogen and oxygen. The hydrogen is then introduced into the air intake to act as a combustion catalyst. “So we’re not replacing diesel we are refining the burn to make it cleaner, cooler, and more complete. “This means less soot, less heat stress on the engine, and reduced emissions right at the combustion stage, not just post exhaust.” What about the maintenance of Ultimate Cell? Gareth: “It’s serviced every 1,200 to 1,500 hours, aligned with regular machine service intervals. At that point, the service team just needs to do a few simple checks and top up the electrolyte.” How have you been working with Lynch Plant Hire? Gareth: “We first trialled the system on different machines in its fleet, and now we already have over 85 units deployed across the Lynch fleet, with more to come. “We now have over 38,000 units operating in 65 countries, helping fleets transition towards a lower-carbon future. Hydrogen’s been around a long time, but now it’s coming to the forefront.” You can also see my interview with James Barden of Lynch talking about adopting the technology here: https://lnkd.in/euEgf5zY #hydrogen #UltimateCell #LynchPlanthire #SustainableEquipment #hydrogeninconstruction James Barden

India's urban congestion is escalating due to the rapid rise in private vehicle ownership. The Ministry of Road Transport & Highways (MoRTH) reported a 9.5% annual growth in vehicle registrations, with Ahmedabad alone seeing over 1.5 lakh new vehicles yearly. This surge calls for a paradigm shift in how we approach urban mobility. Financial sustainability is key to transforming public transport systems into self-sustaining entities. Revenue diversification is crucial, and successful models like Transport for London, which generates substantial revenue through advertising and corporate partnerships, provide valuable insights. Indian systems are adopting similar strategies—premium services, advertising, and monetizing public spaces in metro and bus terminals are becoming vital revenue streams. Public transport networks can also play a role in logistics. The Indian Railways’ shift towards freight corridors, earning more from cargo than passengers, exemplifies this potential. By using existing bus and train networks for cargo, developing parcel hubs, and collaborating with e-commerce platforms, India's transport systems could not only ease urban congestion but also create new revenue streams. The future of mobility lies in multi-modal transport solutions. These integrated systems—comprising buses, trains, cycling, and shared mobility—offer the way forward. Projects like the Ahmedabad and Mumbai Metro expansions are pivotal in this vision. Mumbai's suburban trains, carrying over 7.5 million passengers daily, reduce the need for private vehicles. If replicated across cities, such solutions will be key to alleviating congestion. Cycling presents an untapped opportunity. Global cities like Amsterdam and Copenhagen have set the bar, with over 40% of commuters cycling daily. Indian cities like Indore, Pune, and Bengaluru are already integrating cycling lanes and bike-sharing systems, promoting eco-friendly mobility. This shift can reduce fuel costs, lower pollution, and enhance public health, but challenges like safety concerns and inadequate infrastructure must be addressed. Shared mobility and electric vehicles (EVs) are transforming urban transport. Cities like Paris, where e-scooters replace millions of car trips annually, offer a glimpse into the future. Bengaluru and Hyderabad have already seen a 20-30% increase in shared mobility adoption. India is accelerating this shift with over 2,000 electric buses deployed under the FAME-II scheme in Gujarat. Digitalization plays a critical role in enhancing the efficiency of urban transport. Real-time passenger information, smart ticketing, online payments, and AI-based route optimization are now part of modern transport networks. The evolution of urban mobility in India is not just about reducing traffic but about creating a sustainable, efficient, and integrated transport ecosystem for the future. #publictransportation #electricvehicle #logistics #metro #multimodaltransport

Reducing Steel Logistics Costs in India: Strategic Framework Logistics accounts for 10–20% of steel’s delivered cost and up to 28% of factory cost. Reducing this burden is key to improving competitiveness. A multi-pronged strategy involving infrastructure, modal shifts, digital tools, and policy reforms can yield significant savings. 1. Shift to Rail, Water, and Pipelines Road transport, though flexible, is 2–3x costlier. Rail movement via rakes and sidings can cut costs by 20–30%. Inland waterways (e.g., Ganga, Brahmaputra) save 40–60% for long-haul bulk cargo. Slurry pipelines, at Rs. 80–100/tonne for 250 km, are vastly cheaper than rail or road and must be expanded for inland plants. 2. Leverage PFTs and DFCs Private Freight Terminals reduce first/last-mile costs. Eastern and Western DFCs offer faster, reliable movement. Time-tabled rakes and rake-sharing improve predictability and lower costs. 3. Improve First & Last-Mile Efficiency Rail sidings, Ro-Ro services, and containerization reduce handling loss and costs. Better road access to ports via PPPs boosts multimodal efficiency. 4. Upgrade Infrastructure Developing dedicated rail/road corridors and multimodal logistics parks under Bharatmala and Sagarmala enhances connectivity. Coastal hubs at Vizag, Kandla, Paradip allow direct port loading, avoiding double handling. 5. Adopt Technology Use of Transport Management Systems (TMS), GPS tracking, and AI-based route optimization improves asset utilization and reduces fuel use. Automation in loading/unloading cuts turnaround time and damages. 6. Streamline Supply Chain Set up regional hubs near consumption centers. Aggregate demand to enable full-rake dispatch. Just-in-Time (JIT) inventory models cut warehousing and demurrage. Collaborate with 3PLs for cost-effective delivery and tracking. 7. Align with Policy & Incentives Leverage the National Logistics Policy’s aim to reduce logistics costs to 5–6% of GDP. Tap freight subsidies, tax incentives for logistics infra, GST pass-through, and single-window clearance for sidings and terminals. 8. Optimize Last-Mile & Maintenance Route planning tools reduce last-mile costs. Strategically located warehouses shorten delivery time. Preventive maintenance of fleets improves uptime and fuel efficiency. Impact Snapshot Rail over road: 20–30% cost saving Waterways: 40–60% Route optimization/backhauling: 10–15% Terminal/siding access: 5–10% Conclusion Combining modal shift, infrastructure upgrades, tech adoption, and policy alignment can reduce logistics costs by up to 40%. This is critical to meeting India’s steel production target of 255–300 million tonnes by 2030 and boosting global competitiveness.

How can we apply a practical, urban-realistic way to apply #logistics #postponement in a highly congested, on-demand last-mile network like #Mumbai? In congested cities, postponement is about delaying final movement, routing, and configuration until the last responsible moment. The approach is keep #inventory close but not committed. The centralised approach fails in a mega-city like Mumbai: One DC → citywide delivery. Traffic uncertainty explodes lead time variability. The Postponement-enabled urban model is about Central DC (bulk stock) → Urban Consolidation Centers (UCCs) at city periphery → #MicroFulfilment Centers (MFCs) inside #demandclusters → Final delivery only after order confirmation. The best example can be found in Bulk FMCG or pharma moved at night from Bhiwandi to Andheri / Kurla / Navi Mumbai hubs, but SKU allocation to pin codes happens only after order arrival. The method intensifies with Postponement of #routing & carrier selection, not just dispatch. In Mumbai, route certainty is an illusion. Freeze inventory location early, but postpone route, vehicle, and rider assignment until real-time traffic, rain alerts, local event disruptions (VIP movement, rallies), time of day-traffic signals become themed. The Zomato / Blinkit style logic: Order placed → dynamic rider + route selection → micro-batching of nearby drops. This is logistics postponement via #algorithms, not #warehouses. The next would be to postpone order #consolidation at hyperlocal level. Instead of: one order → one trip, use temporal postponement windows (15–30 minutes), cluster orders by building, society, or lane. The best examples can be found in Residential towers in Powai / Lower Parel: Orders collected till 7:15 pm: single trip → multi-drop → elevator-based batching. This cuts vehicle-km, not just delivery time. But Product postponement can hardly be ignored, where the approach is move generic SKUs, finalize late. This works surprisingly well even in cities, the best examples are: Pharma: strip-level inventory, finalize packs at MFC or Food & QSR: base prep centralized, final assembly near consumption. This reduces wrong-SKU trips or emergency re-routes across the city. But use of time-based postponement, not distance-based is rising. Mumbai logistics works better by time slices than geography. Here the smart play is: Heavy replenishment → night / early morning; On-demand delivery → daytime micro-movements and returns & reverse logistics → off-peak windows. You postpone when you move, not where. But enable postponement with the right control layer. Must-have enablers would be #ControlTower with: Live traffic + weather feeds, Rider density heatmaps, SLA risk alerts by pin code. Also must have Order promising engine that: Adjusts delivery windows dynamically and avoids false speed promises during congestion. In Mumbai, promise accuracy beats speed. But rigid #SLAs kill postponement, better orchestrate customer-enabled postponement. Read my article.

Because wrong service levels and inventory targets kill the supply chain... This infographic shows how to set them up in 7 steps: ✅ 1️⃣ Understand Historical Demand Patterns & Segment the Portfolio 👉 use historical demand data and calculate demand variability. Segment SKUs based on their value and demand variability. ✅ 2️⃣ Define the Required Service Levels 👉 decide the service level targets that the business needs. The higher the service level, more is the inventory needed. ✅ 3️⃣ Determine Lead Times 👉 understand inbound, production and outbound lead times. This will impact how much safety stock the company needs to maintain service levels. ✅ 4️⃣ Apply Seasonal Indexing 👉 Use the formula to calculate safety stock: Z×σd×L ❓ Where: Z is the Z-score corresponding to the service level (e.g., Z=1.65 for 95% service level); σ_d is the standard deviation of demand; L is the lead time in periods. ✅ 5️⃣ Set Reorder Points 👉 calculate Average Lead Time X Average Daily Demand + Safety Stock Calculate reorder points (ROP) to determine when to place an order ✅ 6️⃣ Balance Inventory Targets with Working Capital 👉 use the inventory turnover ratio and days of inventory on hand (DOH) to monitor and set reasonable inventory targets without overstocking. ✅ 7️⃣ Create Feedback Mechanisms & Monitor Performance 👉 track service levels and inventory performance weekly. Identify areas where the targets are not met and safety stock levels, lead times, and demand patterns need adjustments. Any others to add?

Regardless of what side of the AI debate you find yourself. Truth is, AI is here, it’s evolving, and it will become a key component of everything we do in the future. You can’t stop evolution. AI presents numerous opportunities to revolutionize public transportation, paving the way for more efficient, sustainable, and user-friendly systems. Here are some of the key opportunities I’m keeping my eyes on: Optimized Routes and Schedules: AI can dynamically adjust routes and schedules based on real-time data, reducing travel times and improving punctuality. Traffic Flow Management: AI can optimize traffic signals and manage congestion, prioritizing public transportation vehicles and enhancing overall traffic flow. Predictive Maintenance: By predicting and addressing maintenance needs before failures occur, AI can reduce repair costs and extend the lifespan of vehicles and infrastructure. Energy Management: AI can optimize energy usage for electric buses and trains, leading to significant cost savings and reduced environmental impact. Real-time Surveillance: AI-powered video analysis can enhance security by detecting suspicious activities and potential threats in real-time. Incident Prediction and Prevention: AI can predict potential accidents or safety issues, allowing for proactive measures to be taken. Personalized Travel Information: AI can provide personalized travel recommendations, real-time updates, and customer support through chatbots and virtual assistants. Seamless Payment Systems: AI can facilitate smart ticketing systems with dynamic pricing and contactless payments, making the payment process smoother for passengers. Smart Resource Allocation: AI can help deploy resources more efficiently, reducing waste and improving the sustainability of transportation networks. Demand Prediction: AI can analyze patterns to forecast future transportation needs, aiding in better planning and resource allocation. Multi-modal Transport Solutions: AI can integrate various modes of transportation (e.g., buses, trains, bikes, ridesharing) into a cohesive system, providing users with seamless end-to-end travel options. Solving the last mile paradigm. Smart City Initiatives: AI in public transportation can be part of broader smart city initiatives, improving overall urban mobility and connectivity. Enhanced Analytics: AI can process vast amounts of data to provide insights and support decision-making processes for transportation authorities and operators. Performance Monitoring: Continuous monitoring and analysis of system performance can lead to ongoing improvements and innovation in public transportation.