Modified sustainable water management strategy in batch process plants: a case study on reducing freshwater consumption

C_ij

treatment cost/pumping cost of the jth wash from the ith tank

C_wwj

concentration obtained after the jth wash

I

number of storage tanks (i = 1, 2, 3, … N)

J

number of washes (j = 1, 2, 3, … M)

K

number of cycles (k = 1, 2, 3,…)

N

number of treatment technologies (n = 1, 2, 3,…)

S_i

storage capacity of the ith tank

TC_ki

wastewater concentration of the ith tank after the kth cycle

X_kij

binary variable

X_kjn

binary variable

The world is currently grappling with critical challenges such as global warming, fossil fuel depletion, carbon emissions, and water scarcity. Among these, access to potable water stands out as one of the most pressing concerns, particularly for human communities. With growing populations, ensuring access to fresh drinking water has become increasingly challenging, especially in water-scarce regions like India, where water scarcity leads to significant health issues and threatens livelihoods (Singh et al. 2022). To address this, considerable attention has been directed toward sustainable water treatment methods, including desalination, reverse osmosis, and renewable technologies (Davra et al. 2024). Aligned with the United Nations' Sustainable Development Goals (SDGs), ensuring safe drinking water for all by 2030 is a top global priority. However, chemical industries, as major consumers of freshwater, exacerbate water scarcity by generating large volumes of polluted water during various stages, including pre-process, process, and post-process activities like equipment washing and material handling (Desore & Narula 2018; Donoso 2021; Nema et al. 2021). This creates a dual challenge for manufacturers: balancing environmental responsibilities with rising wastewater treatment costs. These challenges can be addressed by minimizing freshwater usage, reducing wastewater generation, and implementing wastewater reuse strategies. Strategic water management and extending reuse practices can significantly reduce freshwater intake and promote sustainable industrial operations.

The pharmaceutical batch process industry generates wastewater with highly variable composition and quantity, depending on the raw materials, manufacturing processes, and seasonal factors. Standard treatment methods in this sector include recovering medicines or solvents and washing fluids, physical–chemical treatments such as flotation, and advanced hybrid technologies. These approaches enable the pharmaceutical industry to mitigate its environmental footprint and contribute to sustainability. Globally, pharmaceutical firms are subject to stringent water quality regulations for internal use, discharge, and recycling. These standards target specific waste contaminants and emphasize the need for pure water in significant quantities. Improper disposal from manufacturing facilities, especially wastewater from fermentation and chemical synthesis processes, contributes to environmental pollution. Maintaining product quality and safety also requires robust cleaning procedures focusing on high-risk contamination stages. Effective cleaning involves selecting suitable cleaning agents based on solubility, equipment type, and residue limits defined by factors such as potency, toxicity, and stability. The pharmaceutical industry can achieve regulatory compliance and environmental sustainability through effective wastewater management and optimized cleaning processes.

Production planning and inadequate wastewater handling methodologies significantly impact on multipurpose batch plants. In batch production industries, considerable amounts of water are utilized in manufacturing processes and cleaning of process equipment (Wang et al. 2010). This dual usage of water underscores the importance of implementing efficient production scheduling and wastewater management practices in multipurpose batch plants to optimize resource utilization and minimize environmental impact (Bagajewicz 2000; Shoaib et al. 2008; Zwain et al. 2018; Akpan et al. 2020; Wang et al. 2023; Shaik et al. 2014). Freshwater intake can be reduced by implementing proper handling and extending the concept of wastewater reuse. By adopting reuse strategies, industries can optimize water usage and minimize their reliance on freshwater sources which contribute to sustainable water management practices (Majozi 2005; Majozi et al. 2006; Gouws & Majozi 2008; Halim & Srinivasan 2010). This approach helps conserve valuable water resources by reducing the overall environmental footprint associated with water consumption (Foo 2008). Reusing opportunities manifest as direct utilization from one processing unit to another or indirect application through central storage vessels. This dual strategy conserves precious freshwater and reduces wastewater production and associated costs (Klemeš 2012; Aguilar-Oropeza et al. 2019). Jacques and Thokozani proposed a methodology to address storage and wastewater generation issues. The first problem focuses on minimizing central storage requirements and the second problem involves minimizing wastewater in the presence of fixed storage. The proposed methodology aims to solve these specific challenges effectively (Gouws & Majozi 2008). Jivani et al. (2021) introduced a methodology for managing wastewater generated by multiple equipment washes and implementing an optimal storage strategy.

The treatment technique is helpful in reducing wastewater generation from plants and reducing contaminants from highly concentrated wastewater. Conventional wastewater treatment methods like the activated sludge process must catch up in completely removing active pharmaceutical ingredients and other wastewater constituents (Gadipelly et al. 2014; Shukshith & Vishal Gupta 2016). In specific industries, diverse treatment plants are established to address variations in the concentration of different elements within wastewater (Sathya et al. 2022). These treatment plants' operation depends on factors such as the quantity and concentration of the wastewater being processed (Michail et al. 2023). This approach allows industries to tailor their treatment processes to the specific characteristics of wastewater, ensuring more efficient and targeted removal of contaminants (Boris et al. 2014). In recent years, scientific research and engineering applications have increasingly focused on advanced and optimal pharmaceutical wastewater treatment. The predominant method employed in this context is physicochemical technology (Yiping & Yu 2010). This approach involves the application of physical or chemical methods such as coagulation, sedimentation, and membrane separation. Various membrane separation techniques are utilized, such as microfiltration, ultrafiltration, and reverse osmosis. These methods effectively remove a broad spectrum of impurities, suspended solids (SS), dissolved inorganic salts, colloids, and various organic substances. Adopting physicochemical technologies and membrane separation techniques reflects a contemporary and comprehensive strategy for addressing challenges of pharmaceutical wastewater treatment (Chopra et al. 2011; Imran 2014; Yan et al. 2014; Guo et al. 2017). Meanwhile, Yang et al. (2014) presented wastewater treatment cost functions to facilitate the optimal selection of treatment techniques. The present study integrates a range of technologies and explores systematic storage solutions for the recycling and reuse of wastewater.

Several researchers have directed their efforts toward the recycling and reuse of wastewater generated during specific processes or within entire industrial plants (Ostad-Ali-Askari & Eslamian 2021; Portman et al. 2022; Gaëtan et al. 2022). Production optimization of batch processes in the presence of environmental criteria, resource constraints, recycling, and reusing of water has received significant attention from researchers (Floudas & Lin 2004; Mendez et al. 2006; Nema et al. 2021; Niu et al. 2022). Drawing inspiration from this scholarly backdrop, the current study is dedicated to the pursuit of reducing wastewater generation and alleviating the need for freshwater intake within the complex operational environment of multiproduct batch plants. This endeavor is in alignment with the overarching goal of reinforcing the sustainability and efficiency of industrial processes. The primary focus of the present model is to curtail quantity wastewater generation resulting from the repeated washing of process equipment while concurrently reducing freshwater consumption, all within the regulatory standards. These efforts are further complicated by environmental constraints, spanning the quality and quantity of water discharge.

The significant increase in water demand emphasizes the urgent need for a more rational and sustainable approach within the chemical industry to manage this scarce natural resource effectively. Formerly reliable sources such as groundwater, rivers, and lakes are now compromised due to chemical and microbial contamination, necessitating careful management of this precious and renewable resource (Bailone et al. 2022). The challenges of water scarcity are further exacerbated by climate change and environmental degradation, affecting routine practices in industries. To mitigate these issues, businesses can adopt water-saving strategies that not only yield environmental benefits but also contribute to long-term cost reduction. In this context, chemical processing industries are pivotal in adopting sustainable water management plans. Cleaner production methods (CPMs) provide a framework to prevent, contain, and minimize the detrimental impact of industrial activities on the environment and society (Bixio & Wintgens 2006).

The chemical industry faces a complex wastewater challenge, marked by high concentrations of organic and inorganic matter, metals, oils, microbial toxicity, and elevated salt levels. Exploring alternative water processing methods that involve recycling and reusing wastewater becomes paramount to address this challenge. Adopting such methods can pave the way for more sustainable and responsible use of water resources in the chemical industry (Hsine et al. 2005).

In recent years, a growing body of research has emerged, focusing mainly on how companies can adapt to the evolving market environment by adopting new production methods and processes centered on sustainability. One prominent concept that has gained traction is Industry 4.0, often called the Fourth Industrial Revolution. This innovative approach mobilizes companies globally to leverage cutting-edge technology, fostering the development of an intelligent production system. The aim is to establish ‘intelligent factories’ characterized by high-quality systems and advanced technology, marking a significant shift in manufacturing paradigms (Borowski 2021).

The current method integrates the scheduling of batch plants, proposed optimal wash water storage strategy and selection of optimal treatment techniques offering a comprehensive approach to water recycling and reusability in multiproduct batch plants. This approach is implemented through an industrial case study aimed at addressing the extended formulation of environmental sustainability within such complex frameworks. The proposed method reduces fluctuations in the influent concentration and flow rates to the end of the pipe treatment helping in optimal selection of waste treatment techniques. The proposed method reduces specific consumptions, minimizes total cost associated with waste treatment in a complex batch process plant helping industries in establish a more efficient and cost-effective environmental management system. This intern contributes significantly to sustainable practices and aids in the reduction of pollution, aligning with broader environmental objectives.

The rest of the article is structured as follows: Section 2 briefs the proposed water management approach, Section 3 discusses case study: water network of commercial pharmaceutical industry, Section 4 explains results and discussion, and finally, Section 5 concludes the article.

In batch operations, the generation of wastewater can vary significantly due to product changeovers, resulting in time-dependent generation rates of contaminant waters. To manage this variability, a buffer system, such as equalization tanks, can be installed to equalize wastewater flow rates and pollutant concentrations simultaneously (McLaughlin et al. 1993). These tanks receive inputs from various batch operations, including spent utility waters or wastewater and serve as feed for wastewater treatment units and discharge points. Wastewater equalization is joint in batch process industries due to its effectiveness in reducing flow fluctuations and concentrations (Nemerow 1971). The design of equalization and segregation tanks depends on the inlet and outlet flow rates of wastewater. These tanks can help stabilize the flow and concentration of wastewater to make treatment processes more efficient. Dhanwani et al. (2015) described a buffer system for simultaneously equalizing wastewater flow rates and pollutant concentrations. In their work, wastewater generated by washing from each plant connected to segregation tanks. They conducted dynamic simulations using MATLAB to analyze the time-varying nature of inlet streams, the height of wastewater, and concentration variations in each segregation tank. This approach allows for a deeper understanding of the dynamics of wastewater generation and aids in designing and optimizing buffer systems for wastewater management in batch operations.

The proposed method directly compares wastewater pollutant concentrations and environmental regulations. Wastewater from multiple unit washings is directed to different storage tanks based on outlet concentration constraints determined by the recycle/reuse strategy. A mathematical model, implemented for a commercial pharmaceutical industry, incorporates dynamic simulations to capture time-varying inlet stream characteristics. These simulations predict wastewater height and concentration variation in segregation tanks, aiding in storage tank optimization and efficient wastewater management strategy development.

The initial one or two washes typically have high outlet concentrations, which significantly reduce with subsequent washes. We propose recycling/reusing low-contaminant water for further unit washing to minimize both freshwater consumption and wastewater generation. Highly contaminated wastewater is directed to the end-of-pipe (EOP) treatment facility. The optimal choice of treatment facility depends on wastewater quantity, pollutant concentration, and operating cost. Effectiveness of different treatment technologies in removing specific pollutants is crucial for decision-making, ensuring efficient pollutant reduction and cost savings while meeting regulatory standards.

As shown in Figure 1, T-1 functions as the reservoir for the wash liquid derived from the first and second washes, which generally carry a higher concentration and thus necessitate treatment before reuse. Similarly, T-2 handles the third wash liquid, which, after being reused, is directed to T-1. This sequential pattern persists as T-3 manages the fourth wash liquid, subsequently cycling to T-2, and so forth. Ultimately, T-4 oversees the management of the last wash liquid, which then transfers to T-3 for additional reuse in the wash cycle.

To address the wastewater management challenge described above, we have developed a mathematical model. This model offers insights into the optimal storage strategy and facilitates the recycling and reuse of water. Additionally, the model optimizes the total cost by considering various parameters. Through this approach, we aim to enhance efficiency, minimize environmental impact, and ensure sustainable water management practices.

Key parameters play vital roles in analyzing wastewater treatment systems. These include the inward flow rate of wastewater for nth treatment unit (Q_in), outlet concentration of the equalization tank (C_equq), removal efficiency (η_n) for contaminant elimination, and final outlet concentrations (d_n). These factors are critical for assessing treatment technology effectiveness, ensuring regulatory compliance, and optimizing overall system efficiency and environmental responsibility in wastewater treatment processes.

The following mathematical parameters are considered while constructing the model.

• Fixed installation cost (A_i): This represents the upfront expenditure for setting up individual tanks or equipment, covering expenses like site preparation and installation labor.

• Cost coefficient of FRP tanks (B): This coefficient determines the cost of fiber-reinforced plastic (FRP) tanks, which are commonly used for storage solutions and vary based on size and specifications.

• Storage capacity (S_i): Crucial for storage tanks, S_i denotes the volume of fluid each tank can accommodate, typically measured in liters.

• Cost coefficient of freshwater (C_w): This is used to calculate the cost associated with freshwater usage in treatment, washing, or storage processes.

• Treatment unit cost (C_tu,n): This represents the cost of each treatment unit, which can vary depending on the type of treatment being considered.

• Capital cost of treatment unit (CI_tu,n): The initial investment needed for procuring and installing a treatment unit, encompassing equipment purchase, installation, and related infrastructure.

• Operating cost of treatment unit (CO_tu,n): Ongoing expenses for each treatment unit, covering maintenance, energy consumption, labor, and other operational costs.

In Equation (12), the outlet flow rate is determined based on the recovery ratio of the treatment technique. Additionally, A represents the membrane area, crucial in filtration and separation processes, while Lt signifies the membrane element's lifetime, aiding in maintenance scheduling and replacement considerations. The pump efficiency (n_p), typically set at 0.8, influences fluid dynamics and flow rates within the system, while feed density (ρ) plays a pivotal role in fluid behavior. C_e represents electricity cost, a fundamental economic factor affecting operational expenses, while H denotes the number of working hours per year, essential for estimating energy consumption. P stands for pressure drop, and C_d reflects waste disposal costs, crucial for environmental and economic reasons. R_n signifies the recovery ratio of the nth treatment unit, guiding decision-making processes to select technologies that are both cost-effective and environmentally sustainable.

Equations (13) and (14) detail the determination of wastewater concentration from specific treatment units, while Equations (15)–(17) impose constraints on the volumetric flow rate into these units. Equations (18)–(20) set constraints on the total concentration within specific tanks after each wash cycle, as it accumulates into a designated storage tank. Equation (21) is a dynamic component crucial for defining the wastewater level (h) within storage tanks, accounting for their cylindrical shape with uniform cross-sectional areas (A) and varying inlet volumetric flow rate (q_i) of generated wastewater, alongside a constant volumetric flow rate (q₀) connected to the EOP treatment plant.

These parameters are vital for determining the flow and management of wastewater. To tackle the complex optimization problem, combination of a mixed-integer programming (MIP) and nonlinear programming (NLP) approach is employed, with support from a General Algebraic Modelling System (GAMS) solver. The time required for optimization by the solver is outlined in Table 1. This mathematical model and its associated constraints offer a structured framework for precise and efficient wastewater treatment and storage strategy management in industrial processes, contributing to both environmental sustainability and cost-effectiveness goals.

The current study focuses on developing a genuine water network model for a commercial pharmaceutical unit at Ankleshwar, Gujarat, India. This approach ensures the study's relevance to the real-world context of the pharmaceutical industry, providing valuable and applicable findings. The model includes multiple products, various process units (e.g., reactor, scrubber, centrifuge, tray dryer), and treatment units such as reverse osmosis (RO), ion exchange (IX), and ultrafiltration (UF) technologies.

The primary aim of the proposed method is to minimize comprehensive costs associated with both freshwater consumption and wastewater treatment through a rigorous approach. This objective is achieved by integrating a short-cut method for treatment units and an optimal storage strategy for wastewater recycling, resulting in optimal outcomes. The proposed water network strategy demonstrates the potential for substantial reductions in freshwater demand and alleviates the strain on treating highly contaminated wastewater units.

The integration of the GAMS-MATLAB interface has been highly beneficial, allowing seamless interaction between GAMS modeling and optimization capabilities and MATLAB's analytical and visualization capabilities. This integration enhances solution efficiency and effectiveness, improving optimization and decision-making processes. Overall, the successful empirical validation of the model and the efficacy of the GAMS-MATLAB interface underscore the robustness and practicality of our approach, contributing significantly to wastewater management knowledge and offering practical solutions for industrial implementation.

In Figure 7, labeled as tank-2, tank-3, and tank-4, a dynamic recycling strategy is presented, demonstrating how wastewater is repurposed for succeeding wash cycles. This recycling approach not only boosts efficiency but also conserves resources and minimizes environmental impact. By reducing treated wastewater volume, we advance toward more sustainable practices.

Water usage for the process unit wash is dependent on the number of washes required. Approximately four water washes are needed during the product changeover operation, with the mean water volume per unit being around 736 L for the existing method. As shown in Table 2, implementing the recycle and reuse method reduces freshwater usage almost 58%.

The present article explores a case study on industrial wastewater treatment systems, supported by numerical evidence and optimization techniques. This study aims to validate the effectiveness of the proposed system. Key insights drawn from the detailed investigation include:

• The study highlights the advantages of integrating multiple intermediate storage tanks within the wastewater management system. Notably, employing more than one intermediate storage tank leads to a significant reduction in freshwater consumption. This achievement directly enhances the overall profitability of the plant.

• Dynamic simulations evaluating variations in wastewater height and concentration levels within the storage tanks. Monitoring wastewater height provides crucial insights into potential risks such as overflow or depletion, enabling proactive management and prevention of operational disruptions. Furthermore, the proposed wastewater management system demonstrates a noteworthy accomplishment with a nearly 58% reduction in freshwater consumption. This reduction yields substantial cost savings and moderates the burden on the ETP by reducing the volume of wastewater requiring treatment.

• Moreover, the study reveals a commendable 57% reduction in variable costs attributed to the diminished load on effluent treatment. The implementation of the proposed method results in a short payback period. Additionally, the study identifies optimal flow rates necessary for specific treatment techniques. These optimized flow rates are crucial in minimizing the overall treatment cost and ensuring strict compliance with government discharge regulations, aligning the plant with regulatory requirements and environmental standards.

• The study underscores the significant economic and environmental benefits of integrating multiple intermediate storage tanks in wastewater management strategies.

The proposed multiple batch plants offer a versatile solution that can be adopted by various chemical industries, small process plants, and other industrial sectors grappling with the challenge of wastewater management. Their adaptability makes them suitable for a wide range of applications, addressing the pressing need for effective wastewater handling. Furthermore, these advancements hold great promise for addressing the evolving needs of industries and ensuring responsible environmental stewardship in the face of wastewater challenges.

All the personnel at the company provided support during the development of the present work.

J.J.: Conceptualization, writing draft, editing. M.S.: Formal analysis, detailed reviewing. A.D.: Formal analysis, detailed reviewing, editing original draft. P.M.: Editing original draft.

The authors declare no external funding or financial support for this work.

All relevant data will be made available to readers on a reasonable request.

The authors declare there is no conflict.