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Storm is a highly skilled player, but there is still one boss he is unable to defeat… Enjoy this short animation by Pablico, followed by a BTS.

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Learn the art of advanced facial rigging from Rik:
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30 maja 2026 roku sygnatariusze z kilkunastu organizacji i nieformalnych inicjatyw, w tym „Kontrabandy”, podpisały deklarację w ramach inicjatywy SPOIWO – Sojuszu Przyjaciół Otwartego i Wolnego Oprogramowania. Nagranie to przedstawia wypowiedzi przynajmniej niektórych podpisujących się pod 10 tezami nowo powstałego ruchu.

Na zdjęciu na miniaturce znajduje się dr Jan Oleszczuk-Zygmuntowicz.

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Wesprzyj „Kontrabandę” na...

– Patronite (jeżeli interesuje Cię wsparcie cykliczne, co miesiąc): patronite.pl/kontrabanda.net
– buycoffee.to (jeżeli chcesz wpłacić tylko jeden raz): buycoffee.to/kontrabanda

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Obserwuj „Kontrabandę” na:
– Mastodonie – mastodon.com.pl/@kontrabanda
– PeerTube'ie – play.kontrabanda.net/a/ch_kont…
– Hejto – hejto.pl/uzytkownik/kontraband…
– YouTube'ie – youtube.com/@kontrabanda_net
– TikToku – tiktok.com/@kontrabanda.net

The aggregate industry is becoming increasingly competitive as infrastructure, mining, and construction projects demand higher productivity and more consistent material quality. Traditionally, aggregate producers relied heavily on operator experience and manual inspections to manage production. While these methods remain valuable, modern technology now allows companies to make more informed decisions through data analysis.

Whether operating a large aggregate crusher plant(chancadora de agregados), a flexible mobile stone crusher plant, or a fully integrated aggregate plant, collecting and analyzing operational data can significantly improve efficiency, reduce costs, and increase profitability. By transforming raw data into actionable insights, plant managers can identify bottlenecks, optimize equipment performance, and make smarter production decisions.

Why Data Analysis Matters in Aggregate Production

Every stage of aggregate production generates valuable information. Crushers, screens, conveyors, feeders, and stockpile management systems all produce data that can be used to improve plant performance.

Many aggregate producers focus primarily on equipment upgrades when seeking productivity improvements. However, analyzing existing operational data often reveals opportunities for significant gains without major capital investment.

Moving From Reactive to Proactive Management

Traditional management approaches often respond to problems after they occur. Equipment failures, production delays, and quality issues are addressed only when they become visible.

Data analysis enables operators to:

• Detect performance trends early
• Identify potential failures before breakdowns occur
• Optimize production planning
• Reduce unexpected downtime

This proactive approach can improve the overall efficiency of an aggregate crusher plant while lowering operating costs.

Monitor Key Production Indicators

The first step in data-driven optimization is identifying the most important performance metrics.

Track Equipment Utilization Rates

One of the most useful indicators is equipment utilization.

Plant managers should monitor:

• Crusher operating hours
• Conveyor running time
• Screen utilization
• Equipment idle periods

In many cases, an aggregate plant may have sufficient installed capacity but fail to achieve expected output because equipment utilization is lower than anticipated.

Measure Actual Production Capacity

Comparing actual production against designed capacity helps identify operational inefficiencies.

For example, if a mobile stone crusher plant(planta de trituración móvil) is rated at 200 tons per hour but consistently produces only 150 tons, data analysis can help determine whether the limitation is caused by feed material, operator practices, or equipment settings.

Identify and Eliminate Production Bottlenecks

Bottlenecks are one of the most common causes of lost productivity in aggregate operations.

Analyze Material Flow Throughout the Plant

Production data can reveal where material flow slows down.

Common bottlenecks include:

• Undersized feeders
• Overloaded screens
• Insufficient conveyor capacity
• Secondary crusher limitations

An aggregate crusher plant can only perform as efficiently as its slowest component. Identifying these constraints allows operators to prioritize improvements where they will have the greatest impact.

Balance Equipment Capacity

A well-designed aggregate plant requires balanced production across all processing stages.

Data analysis helps operators verify that:

• Primary crushing capacity matches downstream equipment
• Screening systems can handle peak throughput
• Stockpile management supports continuous operation

Balanced equipment performance reduces idle time and improves overall plant efficiency.

Improve Maintenance Through Performance Data

Maintenance costs represent a significant portion of aggregate production expenses.

Use Predictive Maintenance Strategies

Modern monitoring systems collect information such as:

• Bearing temperatures
• Motor current consumption
• Vibration levels
• Hydraulic pressure readings

Analyzing these indicators helps maintenance teams identify potential failures before they result in unplanned shutdowns.

Both stationary aggregate crusher plant operations and mobile stone crusher plant units can benefit from predictive maintenance programs that reduce downtime and extend equipment life.

Evaluate Wear Part Performance

Wear components such as jaw plates, cone liners, impact bars, and screen media directly affect productivity.

Data analysis allows operators to:

• Monitor wear rates
• Schedule replacements more accurately
• Reduce emergency maintenance
• Improve spare parts inventory management

These improvements contribute to more stable production performance.

Optimize Product Quality Through Data

Production efficiency is not only about maximizing output. Product quality also plays an important role in profitability.

Monitor Aggregate Gradation

Screening and quality control data can help ensure that products consistently meet customer specifications.

Regular analysis of gradation data enables operators to:

• Adjust crusher settings
• Improve screening efficiency
• Reduce off-spec material
• Increase product value

A data-driven aggregate plant(planta de áridos) can often achieve better quality control than operations relying solely on visual inspections.

Reduce Reprocessing Requirements

Excessive recirculating loads consume energy and reduce plant efficiency.

By analyzing production data, operators can optimize crushing and screening parameters to minimize unnecessary material reprocessing.

Enhance Decision-Making With Real-Time Reporting

Modern plant management increasingly relies on digital dashboards and reporting systems.

Create Actionable Performance Reports

Daily and weekly reports should include:

• Production volumes
• Equipment availability
• Fuel consumption
• Maintenance activities
• Product quality metrics

These reports help managers identify trends and make informed operational decisions.

Improve Coordination Between Departments

Production, maintenance, and quality control teams often work more effectively when they share common performance data.

A unified reporting system enables faster problem-solving and supports continuous improvement across the entire aggregate plant.

Turning Data Into Competitive Advantage

Data analysis is rapidly becoming a key driver of success in the aggregate industry. Whether operating a large aggregate crusher plant, a mobile stone crusher plant serving multiple project locations, or a modern aggregate plant with integrated automation systems, companies that leverage data effectively can achieve significant improvements in productivity and profitability. By monitoring key performance indicators, eliminating bottlenecks, optimizing maintenance, and enhancing product quality, aggregate producers can transform operational data into a powerful tool for sustainable growth and long-term competitiveness.

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While shopping around for the mobile asphalt plant, you should do the best to get a reasonable price. However, this doesn't mean you must compromise on the caliber of your machine only in the interests of a lesser price. This post takes a good look in to the proper research method that will enable you to find your ideal equipment on the best price possible.

To begin with, make sure you are aware of the specifications of your respective ideal mobile asphalt plant. It might be pointless to acquire a plant by using a greater production capacity than you really need. The price difference may be significant, thus it surely repays to gauge your needs before starting to look around for equipment. A 80 TPH mobile asphalt plant may cost you around $200,000, while an 160 TPH one can cost $300,000 or maybe more. You save a good deal on your own investment by simply performing your homework beforehand. Briefly, you must choose the total power of your respective machine, the production capacity, the mixer capacity, the trailing speed along with the trailer quantities. Furthermore, you might want to check out the available options say for example a mobile bitumen tank as well as a mobile filler storage and supplier system.

Also, when comparing different mobile asphalt plants, make sure you check out their fuel consumption, their weighing precision as well as their finished product temperature(planta movil de asfalto). All these parameters possess a direct affect on your operation costs, so you need to optimize them by choosing the right machine. If needed, consider hiring a professional to assist you make the correct choice for your personal business.

Knowing what to search for, you may go on to finding some reliable suppliers. As a rule from the thumb, always attempt to buy this type of equipment from a direct manufacturer. Here is the best method to ensure you'll get yourself a fair price, reliable customer service and faster maintenance(planta de asfalto discontinuo) and repair works whenever needed.

You will discover plenty of suppliers on global trading marketplaces and industrial directories. AliBaba, for example, hosts hundreds otherwise a huge number of constructions equipment manufacturers, every one of them searching for customers worldwide. Through the use of AliBaba, you can purchase your mobile asphalt plant from China and get it shipped to your door, without having additional effort out of your side. This is actually the appeal of globalization we are able to all go shopping for anything you want, from your very convenience of our homes. The beauty of shopping on the web is that you could find ratings and customer reviews for many companies that sell the particular equipment you're considering. You don't need to inquire about client references to boost your chances to create a great purchase. Discover More: aimixgrupo.com/planta-de-asfal…

Lastly, avoid buying your equipment from your first company you discover, irrespective of how good it may well look. Always try to compare at the very least three offers from different sellers, since this is the best way to understand the market for such products. In the event you seriously consider all these details, you'll surely get the best option for your small business.

cross-posted from: feditown.com/post/3071906

Edit: To clarify, this is not my personal blog. It's just intended to raise awareness and spread it around here as well. I just don't believe in editorializing titles

A peculiar tension grips the Ethiopian construction equipment market. Buyers face glossy brochures from multinational brands alongside aggressive offers from regional assemblers. The self loading concrete mixer price differential can reach 40% for ostensibly similar specifications of self loading mixer trucks. This disparity forces a critical question: is the premium for a established name merely a tax on anxiety, or does it purchase genuine operational security? The argument presented here contests conventional wisdom. While brand heritage commands respect, the harsh realities of the Ethiopian operational environment—remote project sites, intermittent grid power, and a fledgling logistics network—demand a reordering of priorities. After-sales value, not the badge on the grille, should dictate procurement decisions. This analysis dissects the price logic through three pragmatic lenses applicable to Addis Ababa contractors and regional developers alike.

1. The Brand Premium Deconstructed: What the Logo Actually Buys

Established manufacturers from Turkey, China, or Europe invest heavily in R&D. Their self loading mixers feature hardened planetary gearboxes, load-sensing hydraulic systems, and proprietary control software. These components reduce the frequency of catastrophic failures. However, the premium price includes costs unrelated to Ethiopian conditions: emissions compliance for European Stage V, dealer margins in three continents, and glossy marketing campaigns. A buyer pays for these whether they operate in the Rift Valley or the Rhine Valley.

1.1 Residual Value Illusion

Proponents argue that branded machines retain higher resale value. This holds in mature markets with established auction houses and equipment valuation standards. Ethiopia lacks this infrastructure. The secondary market remains informal, driven by word-of-mouth and visual inspection. A three-year-old premium brand mixer might sell for 60% of its original price, but finding that buyer consumes weeks of negotiation. Meanwhile, a regional brand unit, purchased at a 40% discount, depreciates little further because its initial cost contained no speculative premium. The resale argument collapses under local market realities.

1.2 Component Standardization Differences

Premium brands often use proprietary hydraulic pumps and electronic control modules. When a sensor fails, the replacement must come from the brand's authorized distributor. Regional brands tend toward off-the-shelf components—common Rexroth pump clones or standard Siemens logic controllers. A mechanic in Hawassa can source these from general industrial suppliers. The brand premium effectively purchases vendor lock-in. For Ethiopian buyers operating beyond the ring road of Addis, this lock-in translates to weeks of downtime awaiting couriered parts.

2. After-Sales Infrastructure: The Undervalued Determinant of Total Cost

Price logic divorced from serviceability is an exercise in fantasy. A self loading mixer shares DNA with a mobile concrete plant. Its weighing system requires calibration. Its drum bearings need regreasing at precise intervals. Its water metering valve demands descaling in hard water regions. The machine generating the lowest initial quote often carries the highest operational risk if the seller lacks a structured after-sales framework. Ethiopian buyers must interrogate not the brand name but the support ecosystem attached to it.

2.1 Parts Availability Velocity

Define the metric: how many hours between a phone call and a critical part arriving at a site 500 kilometers from the capital? A regional supplier with a warehouse in Modjo and a courier contract can achieve 48 hours. A premium brand whose regional hub is in Dubai or Nairobi often requires seven to ten days, plus customs clearance delays at Bole International Airport. The concrete mixer price in Ethiopia should correlate inversely with parts velocity. Yet the opposite is often true: premium brands charge more for slower fulfillment because their logistics prioritize cost containment for themselves, not urgency for the customer.

2.2 Technical Competency Transfer

The most valuable after-sale asset is a trained local mechanic. Does the seller provide documented training for the buyer's own staff? Or does every fault necessitate a paid visit from a factory technician who must fly in from abroad? Regional assemblers frequently embed training into the purchase agreement because they lack a large service fleet. Premium brands often withhold detailed schematics, arguing intellectual property protection. This asymmetry leaves the Ethiopian buyer dependent on a single service source. Argumentatively, the brand that refuses to empower the customer's own team is selling dependency, not value.

3. Price Logic Synthesis: A Framework for Ethiopian Decision-Making

The optimal purchase balances upfront expenditure against projected downtime costs over a three-year horizon. Downtime for a self loading mixer costs an estimated 8,000 Ethiopian Birr per hour in lost production and idle labor, based on 2024 contractor surveys. A brand that reduces annual breakdowns by 20 hours justifies a premium of 160,000 Birr purely on availability grounds. However, if the brand's parts fulfillment adds 72 hours of downtime per failure compared to a regional alternative, that advantage evaporates.

3.1 The Hybrid Procurement Strategy

Discerning Ethiopian buyers should avoid binary brand-or-no-brand thinking. Instead, evaluate each supplier against three weighted criteria: component commonality (40% weighting), parts fulfillment speed (35% weighting), and training provision (25% weighting). Brand heritage receives zero direct weighting. Applying this matrix often favors tier-two Chinese manufacturers with established Ethiopian distribution, or Turkish brands that have invested in local assembly. These occupy the sweet spot: better quality control than backyard assemblers, but without the logistical handicap of distant premium service networks.

3.2 Contractual Safeguards for After-Sales Performance

Negotiate binding service level agreements before signing. Specify maximum response times for remote diagnostics, maximum lead times for critical spares (define the list of 20 critical items), and minimum training hours for operator and mechanic cohorts. Insert penalty clauses—discounts on future purchases or free parts—for missed targets. A seller unwilling to commit to measurable after-sales metrics reveals their true priorities. The argument concludes that after-sales value on the big concrete mixer is not a subjective feeling. It is a set of contractual deliverables. Ethiopian buyers who demand these deliverables will find that brand value becomes a secondary concern, as it should be.

A lecture I gave in Portland, OR, on May 27, 2026.

It was supposed to be recorded. When I arrived, I learned that there was no formal recording plan in place. So I quickly popped open the macOS Screenshot app and recorded the output. I cleaned up the audio (recorded with my MacBook mic) the best I could. So this is only the slides with my voice. I also added the video recording of my Q&A session using Quicktime, which is found at the end.

Talk abstract:

Writing proper alt text is hard. But it doesn’t have to be. There’s a minimum standard and an advanced approach. People who need alt text will appreciate you for the former and love you for the latter.

Alt text is also a whole lot more than the alt attribute. That’s just one of the many ways to make content accessible. In fact, there are a number of considerations for writing great alt text.

In this presentation, I’ll help you understand the spectrum of options so you can take good care of your audience. We’ll walk through implementation methods, phonetics, composition, complex sources, and tackling social media.

Let’s give screen readers and other assistive technologies something to talk about.

I ran compsize on my debian box. Most files on my btrfs drive are around 20 GB. Almost all are uncompressed. I have 6000 files and 221000 regular extents.

Is that too much fragmentation? The ideal case is 1 extent per file.

I am reading around 100 MiBps from the drive out of a theoretical max of ~119 MiBps on a 1 Gbps line.

edit: On a local read I am getting 130-150 MiBps which exceeds the 1 Gbps network. pv /path/to/file >/dev/null

edit 2: For reference, this is a WD Red 6TB drive from around 2018-2020. Max speed should be in the 200 - 250 MBps range.

I defragged a ~300 GB folder and deleted some unneeded files. Extents per file actually went up, but I think that's because the remaining files are heavily fragmented (many 70+ extents per file). Somewhat surprisingly, most/all of the defragged files still had 3-10 extents. Each file is under 2 GB.

Before: ~35 extents per file.
After: 55 extents per file.

compsize /path/to/folder
Processed 2648 files, 145287 regular extents (145287 refs), 1 inline.
Type       Perc     Disk Usage   Uncompressed Referenced
TOTAL       99%      1.5T         1.5T         1.5T
none       100%      1.5T         1.5T         1.5T
zstd        19%      236M         1.1G         1.1G