Having worked in the chlor-alkali industry for many years, I tried to use a simple approach to re-examine those processes that have always been done in the same way

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This post was last edited by xiouxingzhe on 2026-5-5 13:44. Having worked in the chlor-alkali industry for many years, I tried to use a simple approach to re-examine those processes that have always been done in the same way. Dear friends online, as well as those who are experienced in the chlor-alkali industry: Hello everyone! I have worked in the chemical industry within private enterprises for over twenty years. Recently, I compiled the project notes and lessons I had accumulated into a book titled \"Practical Experience and Reflections on Chemical Projects in Private Enterprises: From Strategic Breakthroughs to Lean Operations.\" When it came to writing the chapter on “Innovation and Improvement,” I was stuck for a long time. Because there is one issue that cannot be ignored: for a mature technology like chlor-alkali, where does innovation come from? We don’t see disruptive breakthroughs every day like in emerging industries. What we are dealing with are devices that have been in use for over a decade, parameters specified in the operating procedures, and the practice of \"always having done it this way\" that has been passed down from generation to generation. But I always feel that many of these \"things have always been done this way\" are actually \"safeguards\" put in place back then to deal with uncertainty; over time, those safeguards turned into habits, and habits turned into rules. For example: why should the excess alkali content in a batch of brine be controlled at 0.1–0.3 g/l? Why does the chelating resin column need to be regenerated every 24 hours? Why does salt sludge still require costly landfilling even after being washed over and over again? Behind these seemingly trivial \"small problems\" lies a common dilemma: in order to ensure safety, we incorporate a large amount of \"static redundancy\" into the systems – excessive amounts of medication, extra wastewater generated, and wasted steam. It seems fine in the short term, but when considering the entire life cycle, there is actually a continuous loss of value. I call this phenomenon the “efficiency paradox”. To crack it, a set of thinking methods was developed, named “Four-Dimensional Reshaping”. Put nicely, it’s a method; to be honest, it means taking a step back before taking action and re-examining the problem from four different perspectives: The ultimate question – setting aside inertia and returning to first principles, what is the theoretical limit of this reaction? The remaining distance we still have to cover—is it being hindered by technology, or by habits? Can this theoretical limit be achieved? Question of robustness: Operating conditions can fluctuate, raw materials may change, and equipment will age. When put into practice, will this plan hold up? To achieve it, are ideal conditions required, or is it enough to be able to withstand fluctuations? Be realistic – is it possible to carry out this project? Risk question: Breaking the old balance will inevitably introduce new risks. How can we identify those \"unexpected pitfalls\" in advance and build a firewall before taking action? System question: Is the optimization for a single work section likely to cause extra costs for other sections? Looking at it from the perspective of the entire plant and its whole life cycle, is this really a worthwhile investment? Step by step, we delve deeper and iterate, just like in modeling, to find a solution to the problem. Of course, reasoning alone is not enough; it’s necessary to put it to the test through actual processes. Next, I will report on the three things I did using this approach: Exploration 1: Single saltwater solution – can the amount of alkali added be determined without relying on guesswork? We have always been used to adding more alkali to the saltwater – \"It’s better to waste it than to let it penetrate.\" But if online monitoring and automatic control are properly implemented and the reaction is carried out thoroughly, can the excess alkali amount be brought close to the theoretical value? We tried it on a small device and found that the key isn’t how advanced the control algorithm is, but rather addressing those two long-standing problems of \"uneven mixing\" and \"detection lag\" first. After filling it in, the excess alkali level decreased by nearly an order of magnitude, and the water quality became more stable. Exploration 2: Secondary brine – can resin towers be regenerated without relying on a calendar? Regeneration occurs as soon as 24 hours have passed, regardless of the actual saturation level of the resin. We tried adding a tower for redundancy, letting the online data and models determine the regeneration timing, and the regeneration process was also slowed down. As a result, a significant amount of acid and alkali was saved, the wastewater volume decreased, and the penetration risk was also reduced from \"high risk\" to \"low risk\". Exploration 3: Salt mud treatment – can it be transformed from an expense for landfilling into a valuable resource? Salt sludge has always been a “cost center”. We re-examined the mass transfer mechanism in the washing process, linking homogeneous washing, counter-current washing, and high-pressure filtration into a cohesive sequence. The salt content in the resulting filter cake has been reduced to a level suitable for use in construction materials, and the brine washed out can be reused. This is what touches me the most: often, what is called “waste” is simply something we yet lack the ability to turn into a resource. These three things are merely the result of my personal exploration; if there is any insight to be gained, it has been accumulated gradually through countless attempts and mistakes, as well as lessons learned from reality. The next few tough challenges ahead – I’d also like to hear everyone’s opinions: the decomposition of chlorates; currently, it is mainly done by adding acid and heating, which results in high energy consumption. Are there any peers leading the way in the area of catalytic decomposition or source suppression? Sulfuric acid consumption for chlorine drying: it decreases from 98% to 92% and then to 75%; the greater the concentration gradient, the higher the specific consumption. Where is dry drying (such as using molecular sieves) at? Or are there any of those dilute sulfuric acid distillation and regeneration technologies that can be adapted here? Is it possible to overturn the method of using concentrated sulfuric acid for drying? The “intelligent brain” for steam across the entire plant: Each workshop manages its own steam usage, and steam leakage from relief and drain valves has almost become an \"accepted form of waste.\" If digital twins and intelligent scheduling are applied to the steam pipeline network, how many benefits can be achieved? Initiating a discussion: Of the ideas mentioned above, some I’ve pondered over repeatedly, while others are still swirling around in my mind. There’s still a long way to go before they can be put into practice. So I’m taking the risk of posting this today just to hear everyone’s valuable opinions: 1. Are there any metrics in your workshops that you’ve long considered unreasonable, but no one dares to challenge? 2. Among the directions I listed, which do you think is feasible and which seems too idealistic? Especially since someone is already doing it, could you give us some advice? 3. What is the biggest obstacle to implementing such systematic optimization in your factory? Are they too afraid of something going wrong to take action, or do they think it’s better to sell one more unit of product rather than save that little money? One person’s mental capacity is limited, while the wisdom of an industry is infinite. If you are interested in any of the directions mentioned above, or if you are conducting similar experiments with your own devices, I would really enjoy exchanging ideas with you. Together, let’s fill in some of the “holes” on this old road and raise the “ceiling” a bit.