Design, Modeling, and Simulation of Sustainable Multipurpose Processes: A Rural Agroindustry Case Study

1. Introduction

The design of agroindustrial products at present must consider quality criteria that ensure a safe product for consumers and that the technology used remains consistent with the concept of sustainability. The implementation of process design (PD) for multiple products, or multipurpose design, in the development of new agroindustrial technologies has been scarcely explored. However, since this type of design represents a set of decision-making techniques aimed at allocating available resources to specific tasks according to the products to be manufactured, it offers several advantages. The main issue addressed by this type of design is the determination of production batch size [1]. It is necessary to consider that defining the batch size of the final product at industrial or semi-industrial scale requires incorporating a large number of batches from the same raw material, which generates uncertainty in product traceability.

Traceability is widely recognized as a key element in food supply chains, as it is directly linked to product quality and safety [2]. Considering the relationship between final product batch size and the effort required to trace raw material batches, it is necessary to establish a strategy that enables the definition of batch size while taking into account the impact on traceability. A second issue, present in both single-purpose and multipurpose process design, is environmental sustainability. This concern arises from the scarcity of natural resources and the degradation of environmental quality in terms of health and well-being; therefore, it is necessary to integrate these aspects into the accounting of process design [3].

The possible solutions to the previously mentioned issues lead to the need to consider an extended multipurpose process design that includes principles of anticipation, reflexivity, inclusion, and responsiveness. At the same time, this implies that professionals and institutions involved in design must develop anticipatory, participatory, and integrative capabilities [4]. Current and future requirements of industrial process design demand methodologies that integrate a greater number of criteria, allowing engineers to achieve designs that simultaneously meet diverse specifications, including economic, environmental, and social needs [5].

Authors such as [6], present a procedure to address process design tasks in the sugar industry and its derivatives, considering technical, environmental, and economic criteria through a heuristic approach. In contrast, [7] developed a strategy to reduce quality uncertainty in process design within the sugar industry. Life Cycle Assessment (LCA) is a methodology used to evaluate environmental impacts associated with all stages of a product’s life cycle. Researchers such as [8], have conducted LCA studies on complex manufacturing facilities involving multiple lines and products, where the allocation approach supports the systematic development of multi-scale process models and avoids arbitrary assumptions. Meanwhile, [9] investigated the optimization of multi-path production chains and multi-criteria decision-making through sustainability evaluation using the GREENSCOPE methodology (Gauging Reaction Effectiveness for the Environmental Sustainability of Chemistries with a multi-Objective Process Evaluator). The reviewed literature indicates the absence of a standardized method for allocating resource use and environmental impacts among multiple products, particularly in the food industry.

The value of conducting an LCA of one or several products depends on understanding the environmental consequences of the technological systems responsible for their production; therefore, in order to compare energy and chemical production systems throughout the life cycle, it is necessary to consider the inputs and outputs of materials and energy in the previous and subsequent stages. These extended stages include raw material acquisition, precursor manufacturing, product manufacturing, transportation, use, and end of life [8]. Meanwhile, to analyze the multidimensional impacts of process design and operation, researchers from the Environmental Protection Agency (EPA) developed the GREENSCOPE methodology and tool. These sets of indicators, defined mathematically, represent a quantifiable measure of sustainability of process performance, raw materials, utilities, equipment, and output information. This approach uses a dimensionless sustainability scale that provides indicator results as percentage scores (0–100% sustainability) [10].

The GREENSCOPE methodology can be applied flexibly to a process, subprocess, or equipment, and the user can apply GREENSCOPE at any point, from conceptual design. This flexibility makes possible a direct comparison between several processes that manufacture the same product but use different raw materials, reaction processes, separation technologies, or generate different emissions and wastes. In addition, this methodology can be implemented to evaluate sustainability performance before or after making modifications in the process [9].

In most panela-producing facilities, non-centrifugal sugar is obtained in block and granulated forms (granulated panela, GP), and only rarely sugarcane honey (SH). The agroindustry of GP and SH is rural, traditional, and artisanal worldwide, characterized by poorly organized production, where process conditions, final product characteristics, and sustainability indicators are not controlled [11]. The planning and scheduling of design processes in medium-scale or artisanal production are not supported by tools that ensure efficiency and effectiveness in operational development. However, there is market potential for organic sweeteners due to the popularity and importance of sugarcane-derived sweeteners in human diets. In addition, the trend toward consuming healthier foods and reducing refined sugar intake opens the possibility of introducing substitute products such as GP and SH, since they contain fewer calories than sugar and honey and are also more economical [12]. Quality in GP and SH as an early stage in PD and its consideration as a parameter remains poorly documented. In the Amazon region of Ecuador, there are products that share a common technological process base; for example, the production of GP and SH shares unit operations and processes, and another case is the production of ethanol, agricultural rum, and fuel bioethanol. Therefore, the implementation of multipurpose process design would provide effective and efficient algorithms that ensure the quality of multiple food products [13].

The objective of this research was to propose a methodology for the design of sustainable multipurpose processes using process simulation and GREENSCOPE. For this purpose, a case study was taken as a basis through a multipurpose simulation of GP and SH from sugarcane in the locality of Pastaza, considering in this design their quality attributes and the operating conditions of the technological process for different production quantities of both products.

2. Materials and Methods

Methodological Criteria for Process Design and/or Simulation

The methodology used was a modification of the proposal presented in [14]. Both procedures are combined and complement each other for the design of a multipurpose process [15] supported by the GREENSCOPE tool, as shown in Figure 1. The actions, tools, and objectives of each of the steps used are described below. The actions, tools, and objectives of each of the steps used are presented in Table S1.

Generation of Multipurpose Design Alternatives

In the multipurpose design, three types of batches of 10, 120, and 1560 were determined, as in the work proposed by [16]. A batch of 10 corresponds to one day of production, 120 corresponds to one month, and 1560 corresponds to one year. The three types of batches were divided into (20% GP and 80% SH), (40% GP and 60% SH), (60% GP and 40% SH), (80% GP and 20% SH), 100% GP, and 100% SH. Each multipurpose batch was simulated five times (Table 1). The common unit operations in the multipurpose process were programmed in a script. The proposed equations were grouped into mass balances, energy balances, equipment design, environmental indicators, economic analysis, models for quality attributes, sigma level determination, and defective lots per million opportunities (DPMO) [7].

3. Results

3.1 Demanded Products

Granulated panela (GP) and sugarcane honey (SH) were identified as the demanded products considered in the multipurpose process. [17] reported that 24.06% of the surveyed population preferred granulated panela, whereas 2.83% consumed other sweeteners, including sugarcane honey. No official records of the annual production of GP and SH in Ecuador were identified in the reviewed sources.

The quality criteria selected for GP were 83% sucrose and 3% moisture, according to [18]. At the international level, product color was related to the ICUMSA unit through the mathematical model proposed by [19] (Equation 2). For SH, [20] establishes a reducing sugar content of 59% and a moisture content of 26.5%. Viscosity, flavor, and crystal presence were defined as organoleptic quality attributes and calculated using the models reported by [21] (Equations 3–5).

$$\begin{gathered} ColFin=559.688+\left(0.913911\right(-10679.6+\left(2069.52pHEvap4\right)+ \\ \left(20.082TiempDCEvap4\right)-\left(8.9434TfEvap4\right)+\left(69.2559TfEvap3\right)\left)\right)- \\ (64.4582\mathrm{pHCrystGP})+(124.853\mathrm{tAgCrystGP})+(31.2631\mathrm{TfCrystGP})- \\ (20.039TfEvap4) \end{gathered}$$

(2)

$$\begin{gathered} V=-10806.86-37.56pH+0.33{pH}^2+\mathrm{287,14}Brix-1.90{Brix}^2 \\ +0.45BrixpH \end{gathered}$$

(3)

$$S=144.68+115.69pH-13.13{pH}^2-9.98Brix+0.06{Brix}^2-0.04BrixpH$$

(4)

$$\begin{gathered} C=-4092.39+22.46pH-3.79{pH}^2+108.38Brix-0.72{Brix}^2 \\ -0.07BrixpH \end{gathered}$$

(5)

3.2 Technology Selection

The technology selected for SH production corresponded to the process proposed by [7] (Figure 2A). The process begins with sugarcane milling, where the juice is extracted and bagasse is obtained as a by-product. The juice is filtered to remove bagacillo and other impurities, followed by clarification using mucilage. During heating, CaCO₃ is added to regulate acidity and facilitate impurity removal. The clarified juice then passes through three successive evaporation stages until reaching 74–78 °Brix. The final stages include cooling and the addition of citric acid. Acid hydrolysis is applied to maintain the sucrose content below 60% (w/w) and prevent crystallization, according to [21].

The technology selected for GP production corresponded to the process proposed by [22] (Figure 2B). The process begins with sugarcane milling, where the juice is extracted and bagasse is separated. The juice is filtered to remove bagacillo and other impurities, followed by clarification using mucilage. During heating, CaCO₃ is added to regulate acidity to pH 5.8 and facilitate impurity removal. The clarified juice then passes through three evaporation stages, reaching 65–75 °Brix. The concentration stage begins when soluble solids reach 88–92 °Brix, followed by crystallization until values between 92 and 94 °Brix are obtained.

3.3 Are There Common Unit Operations and Processes?

GP and SH share a common processing sequence that begins with sugarcane milling, where juice is extracted and bagasse is obtained as a by-product. The extracted juice passes through filtration to remove bagasse and other impurities [23], followed by heating and three successive evaporation stages [16]. During heating, CaCO₃ is added to regulate the pH of the sugarcane juice [11]. Milling, filtration, heating, evaporation 1, evaporation 2, evaporation 3, and CaCO₃ addition were identified as the common operations and processes involved in GP and SH production (Figure 3).

3.4 Multipurpose Design

The identification of common and product-specific operations supported the selection of a multipurpose process design. For SH production, the specific operations comprise cooling and acid hydrolysis through the addition of citric acid (C₆H₈O₇). For GP production, the specific operations comprise concentration, where soluble solids reach 88–92 °Brix [11], and crystallization, where values between 92 and 94 °Brix are obtained [22]. Therefore, the common processing stages can be integrated into a shared production line, while cooling and hydrolysis are assigned to the SH route and concentration and crystallization are assigned to the GP route (Figure 3).

3.5 Definition of the Technological Scheme

After identifying the common and specific unit operations, the multipurpose technological scheme was defined (Figure 4). In agreement with [24], the proposed scheme corresponds to a multipurpose process in which the products do not necessarily follow the same sequence of operations or require all stages of the production process. Under this arrangement, different products can be obtained simultaneously, and each product may follow a different route within the technological process.

3.6 Capacity Estimation

According to [25] , for each cultivated hectare, between 70 and 100 t of sugarcane are obtained (Table 3), and for each ton of sugarcane, a yield between 58 and 63% can be achieved [26]. Therefore, an average of 102,953.62–133,706 t of sugarcane and 59,713.10–84,234.78 t of sugarcane juice are available in the main parishes of Pastaza. A tentative multipurpose production capacity of 2,000 kg of juice is estimated.

3.7 Macrolocation

According to [27], Tarqui recorded the largest sugarcane cultivation area among the analyzed parishes, with 198.75 ha (Table 3). Based on the availability of raw material, Tarqui was selected as the macrolocation for the proposed multipurpose plant.

3.8 Mass and Energy Balance

Mass and energy balances were performed across the unit operations included in the multipurpose process. A total of 1,155.89 kg of sugarcane at 15 °Brix entered the milling stage. Juice extraction generated 809.12 kg of sugarcane juice and 346.76 kg of bagasse, equivalent to mass fractions of 70.00 and 30.00%, respectively. The difference of 0.01 kg between the inlet and outlet streams was associated with numerical rounding. During filtration, 54.48 kg of bagasse and suspended impurities were removed, leaving 754.64 kg of filtered juice. The calculated mass recovery during filtration was 93.27%, while the separated solid fraction represented 6.73% of the juice entering this operation.

The filtered juice entered the heating stage at pH 5.5. Water removal increased the concentration of soluble solids throughout the evaporation sequence. The stream associated with evaporator 1 reached 148.45 kg at 25 °Brix, followed by 133.17 kg at 38 °Brix in evaporator 2. The outlet stream from evaporator 3 was 116.09 kg at 78 °Brix. Mass reductions of 10.29 and 12.83% were calculated between evaporators 1–2 and 2–3, respectively. The 116.09 kg stream leaving evaporator 3 represented the common basis used to distribute the material between the GP and SH processing routes (Table 4).

The complete stream from evaporator 3 was directed toward the GP route in the 100% GP–0% SH configuration, producing 101.29 kg after concentration and crystallization. This value represented a mass recovery of 87.25% relative to the stream entering the product-specific operations. In the 0% GP–100% SH configuration, the entire 116.09 kg stream was assigned to cooling and hydrolysis. Intermediate configurations distributed the common stream according to the predefined production proportions. The SH stream decreased from 92.87 to 23.21 kg when its participation changed from 80 to 20%, while the stream directed toward the GP route increased from 23.21 to 92.87 kg. Final GP production increased from 20.38 to 81.31 kg under the same configurations, with calculated recoveries between 87.55 and 87.82% after concentration and crystallization (Table 4).

3.8.1 Quality Performance of SH

Process capability was evaluated through the sigma level and defective lots per million opportunities (DPMO), according to [28]. A sigma level equal to or greater than 3 was established as the acceptance criterion. Simulations producing at least one quality response below this limit were repeated using a new combination of randomly generated operating conditions.

The SH simulation generated Beta-distributed values within pH 3.5–4.5 and soluble solids concentrations of 74–78 °Brix, according to the operating intervals reported by [7]. Viscosity, flavor, and crystal presence were calculated simultaneously using the respective response models (Equations 3–5). Acceptance of a simulated batch required the three quality attributes to satisfy the predefined sigma-level criterion.

The configurations containing 100% SH required additional iterations in the groups of 10, 120, and 1560 batches. Additional repetitions were also recorded in the multipurpose configurations containing SH. The occurrence of a new iteration depended on the combined response of viscosity, flavor, and crystal presence under the randomly generated pH and °Brix conditions. The behavior of the three quality attributes across the simulated production configurations is presented in Figure 5 (Figure 5).

3.8.2 Quality Performance of GP

The GP simulation incorporated operating limits associated with ICUMSA color development during concentration and crystallization. Beta-distributed values in the concentrator ranged from pH 5.5 to 7.0, soluble solids from 89 to 93 °Brix, and processing time from 20 to 30 min. The crystallizer operated within pH 5.5–7.0, soluble solids concentrations of 90–94 °Brix, agitation times of 10–20 min, and temperatures of 40–60 °C.

An acceptance interval of 7,000–12,000 ICUMSA units was established together with a sigma level equal to or greater than 3. The 100% GP configurations reached the required quality level without additional iterations. Multipurpose configurations presented iterations when the simultaneous SH responses failed to satisfy the acceptance criterion, because the quality attributes of both products were evaluated within the same computational run.

The concentration stage reached pH 6.4 and 91.65 °Brix, values located within the programmed operating intervals. During crystallization, pH varied from 5.70 to 6.98, while soluble solids reached 94.23 °Brix. The pH values remained within the established limits, whereas the soluble solids response exceeded the predefined upper value by 0.23 °Brix. The ICUMSA responses obtained for the production proportions and the three batch groups are presented in Figure 6 (Figure 6).

3.8.1 Gantt Diagram of the Multipurpose Process

Based on the mass balances of the process, the production times of the multipurpose stages were determined. In Figure 7, the Gantt diagram shows that the production of 60% GP – 40% SH begins with milling at 1:00 AM, lasting 30 minutes until 1:30 AM, followed by filtration from 1:10 AM to 1:40 AM. Heating then occurs from 1:20 AM to 1:50 AM, followed by three evaporation stages of 30 minutes each until 3:20 AM. Cooling takes place from 3:20 AM to 3:50 AM, hydrolysis from 3:50 AM to 4:10 AM, concentration from 3:20 AM to 3:50 AM, and finally crystallization from 3:50 AM to 4:10 AM.

In contrast, the production of 100% GP – 0% SH omits cooling and hydrolysis, starting with milling at 3:50 AM and ending with crystallization at 7:21 AM. Finally, the production of 0% GP – 100% SH does not include concentration or crystallization, beginning with milling at 7:01 AM and ending with hydrolysis at 9:56 AM. In comparison, exclusive SH production is the shortest process due to the absence of concentration and crystallization, GP-only production has a longer duration due to crystallization, and multipurpose production includes all unit operations, resulting in a more extensive and versatile process.

3.9 Availability of Raw Materials

There is an availability of 59,713.10–84,234.78 t of sugarcane juice in the province of Pastaza. The consumption of sugarcane juice in the technological process is 809.12 kg of sugarcane; therefore, raw material availability for the implementation of the technological process is ensured.

3.10 Environmentally Compatible LCA

Environmental indicators were calculated for the production scenarios of 10, 120, and 1560 batches. The variables included raw material consumption, sugarcane juice consumption, energy demand, solid waste discharge, and gaseous residue generation. Similar numerical patterns were obtained among the three batch sizes, although the indicator values varied according to the GP–SH production ratio (Table 5).

The highest GP-related values occurred in the 20% GP–80% SH configuration, with 56.70 kg sugarcane/kg GP, 37.01 kg juice/kg GP, 14,226.51 J/kg GP, 19.68 kg solid residues/kg GP, and 31.41 kg gaseous residues/kg GP. The highest SH-related values were obtained in the 80% GP–20% SH configuration, reaching 49.78 kg sugarcane/kg SH, 32.50 kg juice/kg SH, 12,361.77 J/kg SH, 17.28 kg solid residues/kg SH, and 27.50 kg gaseous residues/kg SH (Table 5).

3.11 Technological Modifications

The simulation results supported the modification of the operating conditions applied in the traditional multipurpose process. The proposed adjustments included the control of pH, soluble solids concentration, and temperature during evaporation, concentration, hydrolysis, and crystallization. A final color response of 7,560.30 IU was obtained for GP, while SH reached 75.6 °Brix. These values were selected as process-control references for obtaining the required quality attributes without replacing the common technological sequence.

3.12 Equipment Design, Availability, and Acquisition Cost

The heat-transfer areas of the equipment associated with the common processing stages remained constant across the three batch sizes and the simulated GP–SH configurations. The calculated areas were 0.62 m² for the filter, 0.97 m² for the heater, and 3.94, 0.15, and 0.19 m² for evaporators 1, 2, and 3, respectively.

The areas of the product-specific equipment varied according to the proportion of GP. The concentrator area increased from 0.08 m² in the 20% GP–80% SH configuration to 0.54 m² in the 100% GP–0% SH configuration. The crystallizer area increased from 0.24 to 1.18 m² within the same production range. No concentrator or crystallizer was required for the 0% GP–100% SH configuration because these operations are not included in the SH production route (Table 6).

3.13 Automatic Control

The selected control variables were pH and °Brix in the feed juice and intermediate streams [29]. The SH route included °Brix control during evaporation, while the GP route included °Brix at the outlet of evaporator 4, agitation time, and crystallizer temperature [7,30].

3.14 Economic Analysis of Investment and Production

Equipment acquisition costs remained unchanged across the three batch sizes for each production configuration. The highest cost corresponded to 100% GP–0% SH, with USD 24,300.52, while the lowest value was obtained for 20% GP–80% SH, with USD 7,873.76. The remaining multipurpose configurations presented costs between USD 12,755.28 and USD 19,494.77, whereas 100% SH required USD 18,396.80 (Table 7).

Total investment cost varied among the production configurations (Figure 8). The 100% GP configuration reached USD 265,496.58, followed by 100% SH with USD 239,809.37. The multipurpose configurations ranged from USD 70,181.40 for 20% GP–80% SH to USD 187,720.95 for 80% GP–20% SH. The 60% GP–40% SH configuration required an investment of USD 140,133.25.

Unit production costs were USD 1.10/kg for GP and USD 0.83/kg for SH. A profit margin of 17% was applied according to Mortimer and Weeks (2019), resulting in selling prices of USD 1.29/kg for GP and USD 0.97/kg for SH. Annual costs included raw materials, labor, packaging, labeling, manufacturing, distribution, and sales (Table 8).

The annual GP cost increased from USD 36,592.48 to USD 75,858.23 as its participation increased from 20 to 80%, reaching USD 88,940.80 in the 100% GP configuration. The annual SH cost decreased from USD 158,456.49 to USD 64,474.81 as its participation declined from 80 to 20%, while the 100% SH configuration reached USD 200,834.64 (Table 8).

3.15 Economically Feasible Alternative

Economic feasibility was evaluated using NPV, IRR, DPP, and profit margin, according to [31]. All simulated configurations presented positive NPV values, ranging from USD 38,295.04 to USD 141,014.59, while IRR ranged from 22.21 to 45.80%. DPP varied between 1.00 and 2.65 years, and profit margin ranged from 0.13 to 0.30 (Table 9).

The highest NPV was obtained for the 120-batch configuration with 60% GP–40% SH, reaching USD 141,014.59. This alternative also presented the highest IRR and profit margin, with values of 45.80% and 0.30, respectively, and a DPP of 1.36 years. The next highest NPV values corresponded to the 10-batch configurations with 80% GP–20% SH and 40% GP–60% SH, reaching USD 136,566.51 and USD 135,432.36, respectively (Table 9).

3.16 Existence of Other Technologies and New Capacities

The selection of the GP technology proposed by [22], was mainly based on the study area, the province of Pastaza, due to the limited availability of scientific literature on GP production in the region. An additional advantage of this work is the possibility of comparing results within the same study context. The selection of the SH technology proposed by [7], was based on its simulation approach, where random values with Beta distribution are generated. Other studies were not considered because few works relate the three quality attributes analyzed in SH. The selected study allows comparison of sigma levels with the present work.

New capacities were not evaluated because economic and environmental indicators, as well as quality attributes, were favorable. In addition, five simulations per batch were considered sufficient. Each multipurpose configuration involved 15 simulations, resulting in a total of 90 simulations, excluding additional iterations required when the sigma level was lower than 3.

3.17 General Greenscope Análisis

The 120-batch configuration with 60% GP–40% SH was selected for the GREENSCOPE assessment because it achieved the highest economic profitability. The indicators were normalized between 0% and 100%, where 0% represents the least favorable reference condition and 100% represents the best condition [14]. Health Hazard–irritation factor (HHirritation), Health Hazard–chronic toxicity factor (HHchronic toxicity), Safety Hazard–acute toxicity (SHacute tox), and Global Warming Potential (GWP) reached 100%, while the aquatic oxygen-demand indicator (WPO₂ dem.) reached approximately 40% (Figure 9).

Specific Energy Intensity (RSEI) reached 78%, Energy Intensity (RIE) reached 20%, and the Renewability–Exergy Index (RIEx) reached 57%. Mass Intensity (MI) recorded approximately 95%, whereas the Renewability–Material Index (RIM) and Fractional Water Consumption (FWC) reached 100%. The economic indicator Turnover Ratio (TR) also obtained a normalized score of 100% (Figure 9).

3.18 Optimal Technology and Capacity

Investment costs and economic indicators were compared across the evaluated production configurations using Figure 8 and Table 9. The 120-batch configuration with 60% GP–40% SH was selected because it achieved the highest net present value (NPV) of USD 141,014.59, internal rate of return (IRR) of 45.80%, and profit margin of 0.30. This configuration presented a discounted payback period (DPP) of 1.36 years and required a total investment of USD 140,133.25.

The GREENSCOPE assessment showed favorable scores for several environmental, material-efficiency, and economic indicators, although the energy indicators presented lower normalized values (Figure 9). Based on the combined technical, economic, and sustainability results, the 120-batch configuration with 60% GP–40% SH was selected as the preferred alternative among the evaluated scenarios.

4. Discussion

The constant flow of 116.09 kg at the outlet of evaporator 3 indicates that changes in the GP–SH production ratio did not modify the upstream mass balance. Product differentiation began after the third evaporation stage through the allocation of the concentrated stream to cooling and hydrolysis or to concentration and crystallization. This arrangement supports the integration of milling, filtration, heating, and evaporation within a common processing line. The calculated behavior agreed with the technological sequence reported by [16].

The additional iterations recorded in SH were associated with the simultaneous evaluation of three response variables. A simulated condition was rejected when viscosity, flavor, or crystal presence failed to reach the established sigma level. The combined dependence of these responses on pH and °Brix reduced the number of acceptable operating combinations. The difference from [7] may be associated with the multipurpose simulation structure, where shared operations and two final product routes were evaluated within the same computational procedure.

The absence of additional iterations in the 100% GP configurations indicates greater stability of the ICUMSA response within the programmed ranges. The ICUMSA values were consistent with the acceptance interval reported by [19], while the pH and °Brix conditions were close to those described by [22]. However, the value of 94.23 °Brix obtained during crystallization exceeded the predefined upper limit by 0.23 °Brix. This deviation requires verification before defining the final operating interval, because excessive concentration may modify crystallization behavior and the physical characteristics of GP.

The highest unit environmental indicators were recorded when GP or SH represented the minority product in the multipurpose configuration. This behavior was associated with the allocation of shared material and energy requirements to a smaller product mass. Bagasses were the main solid residues, while water vapor originated during juice concentration. [32] reported that panela processing can also generate effluents with high BOD, COD, and suspended solids. [33] estimated wastewater generation near 1,000 L/t of product in sugar processing. These studies support the need to include liquid-effluent treatment, although BOD, COD, and wastewater volume were not directly quantified in the present simulation.

The simulated quality responses were consistent with the operating conditions reported by [30] for GP and [12] for SH. This agreement indicates that the proposed modifications can be incorporated through better control of pH, °Brix, and temperature while retaining the existing unit operations. Their application may support process standardization and reduce variability in artisanal production.

The constant areas calculated for the shared equipment were consistent with the values reported by [12], supporting the mass-flow and thermal assumptions applied to the common processing stages. The increase in concentrator and crystallizer areas was associated with the larger material flow assigned to the GP route. Deviations from the correlations proposed by [34] may be related to their application at capacities below the industrial scale. Larger heat-transfer areas also increase acquisition costs because equipment-cost correlations depend on size and processing capacity.

The higher total investment associated with 100% GP was related to the concentrator and crystallizer required in its production route. The 100% SH configuration presented the second-highest investment because the complete mass flow of 116.09 kg per batch was processed through its specific operations. Multipurpose configurations reduced investment through the shared use of milling, filtration, heating, and evaporation equipment. The cost variations in Table 8 were associated with the production proportion assigned to each product and the allocation of fixed and operating expenses. Equipment-cost estimation followed the capacity-scaling procedure reported by [34].

The positive NPV values indicate that all simulated configurations recovered the initial investment and generated economic returns under the assumptions applied. The 120-batch configuration with 60% GP–40% SH presented the best combined performance because it reached the highest NPV, IRR, and profit margin. The estimated NPV values were comparable with those reported by [12]. The variation among configurations indicates that profitability depended on batch size, product proportion, production costs, and expected revenues rather than following the increasing pattern observed in equipment size and investment cost.

5. Conclusions

The integration of process simulation and GREENSCOPE enabled the technical, economic, environmental, energy, and material-efficiency assessment of the multipurpose process. Simulation reduced uncertainty in the quality responses of GP and SH through iterative adjustment of operating conditions until the established sigma-level criterion was achieved. GREENSCOPE complemented the process evaluation using normalized sustainability indicators rather than production stages.

Among the evaluated alternatives, the 120-batch configuration with 60% GP–40% SH presented the best economic performance, with an NPV of USD 141,014.59, an IRR of 45.80%, a DPP of 1.36 years, a profit margin of 0.30, and an investment cost of USD 140,133.25. This configuration reached a sigma level of 3.8. SH presented a pH range of 3.76–4.22 and soluble solids of 76.5–78 °Brix, while GP reached pH values of 5.70–6.98 and soluble solids of 92.4–94.23 °Brix.

The GREENSCOPE assessment showed favorable normalized performance for HHirritation, HHchronic toxicity, SHacute tox, GWP, RIM, FWC, and TR. The values of 100% represented the best reference condition and did not indicate maximum toxicity or environmental damage. The lower scores obtained for energy intensity, renewable exergy, and aquatic oxygen demand identified energy use and liquid-effluent management as the main areas requiring technological improvement.

6. Patents

This section is not mandatory but may be added if there are patents resulting from the work reported in this manuscript.