Sustainable development is defined as development that ensures the needs of the present without compromising the ability of future generations to face their own needs [1]. This implies an adequate planning regarding the use of resources in the short, medium and long term, and requires an analysis of the threats and opportunities of human beings acting on their environment. Sustainable development seeks a balance between economic growth, social progress and ecological balance [2], this is known as the three pillars on which sustainability is based and contributes to an increase in the welfare and progress of present and future generations [2,3].

Sustainable companies, which use the World Business Council for Sustainable Development as a global regulatory body, are important players in the search for a sustainable world as they care able to develop cleaner production processes that have a positive impact on the environment. A sustainable business creates economic, environmental and social value in the short and long term, thus contributing to the increasing welfare and progress of present and future generations [4].

This article aims to build a model that allows the integration of different elements that interact within the organization and operation of a company, incorporating elements of business sustainability, all with an emphasis on the production process. The main variables and their interrelationships will be identified, allowing decision making that favorably influences the development of the environment and improves the sustainability conditions of the business.

Considering the model was structured in a global manner and under the system dynamics approach, its description and analysis is the basis for its application in other companies of lesser or greater complexity. Moreover, it integrates components of sustainable development with the manufacturing process and the quantitative model.

The model’s construction is based on the characterization of aspects related to sustainable development and business sustainability, while the modeling blueprints with respect to business sustainability and the fundamentals of system dynamics. It continues with the identification of variables and their relationships through the causal diagram, the explanation of the model, and its composition and interrelations based on the structure and functioning of a manufacturing company which served as a reference for data collection and modeling. Finally, the analysis and results of the simulation and the evaluation of the model are laid out.

Based on the records of monthly production, it was found that the production orders were adjusted to a normal distribution with an average and deviation of approximately 39,000 and 8400 units respectively, with minimum reference values of 20,000 and a maximum of 65,000. With reference to the above information, the orders were generated randomly (Fig. 6) following a normal distribution. It was observed that the minimum value generated is 20,868 and the maximum value 58,913. To this end, a process of orders was simulated, coherent with a realsitic context of a company woth a 48- onth outlook.

Figure 6 / Source: The authors

The production order determines the levels of receipt of raw materials factoring in the losses of raw materials, which, in turn, is defined by the rate of material loss and the levels of personnel training. This means that there is a difference between the production orders and the receipt of materials. This difference also means that production levels are lower than the order, leaving products pending for the next production order. To correct this situation, it can be established that the production orders include, from the beginning, the additional percentage of raw materials necessary to satisfy the volumes of products requested. On the other hand, production is also affected by the size of the production order. This is due to the fact that there is a production limit value (PLV), in this case of 35,000 monthly units that, when exceeded, the effectiveness of control over the quality levels of some products is lost. Therefore, the efficiency of the productive process is also affected. The production loss factor keeps increasing until it doubles.

With respect to the inventory of finished products (Fig. 7), it is observed that these are accumulated despite the fact that there is a constant dynamic of products being dispatched.

Figure 7 Source: The authors

The accumulation of finished products is the result of several aspects, including: the policy on product consignment for some clients that are influential and have high levels of contracts with the company, and the impossibility of quickly dispatching all products to customers which affects demand in the long term.

The products which are in the inventory of finished products are sent to customers based on the maximum time of permanence in the inventory, which is 3 months. The dispatching of finished products (Fig. 8) has a consistent behavior with the inventory of finished products, since the shipments depend essentially on the quantity of products that are in the inventory, the time of permanence, and the client’s requirements.

Figure 8 Source: The authors

With regards to energy consumption, this depends on the levels of production and energy consumption per unit. However, it can be modified through training processes where operators can upgrade their work and make better use of their time, which contributes to energy saving. In the same way, the use of technology is an alternative that can contribute to cost reduction through a more efficient use of energy. While measures are not implemented in the energy saving factor of technology (equal to 0), this will accumulate over time without variations in the slope (Fig. 9).

Figure 9 Source: The authors

When a consumption goal of 6 million kwh (the reference value of the company from which the energy saving technology is applied) and a saving factor of 0.1 (Fig. 10) are established, it is observed that the slope changes to a lower value compared to what is observed in Fig. 9.

Figure 10 Source: The authors

When establishing a technology saving factor equal to 0.3 (Fig. 11), it is observed that the slope changes to a lower value after period 12. With a technological energy saving factor of 0.5 (Fig. 12), the value of the slope decreases from period 9, an impact that will be reflected over time.

Figure 11 Source: The authors

Figure 12 Source: The authors

When evaluating the energy cost factor of producing a unit in front of the variations that occur in the technology energy saving factor, rational changes are visualized in Figs. 13, 14, 15 and 16. In the first case (Fig. 13), When the technology energy saving factor is zero, the energy cost factor of producing a unit decreases a little at the beginning ($20); later, from period 3 it maintains a marginal decreasing trend with minimal variations. In the second case, when this factor is 0.01 (Fig. 14), similar to the previous case (Fig. 13), the energy cost factor of producing a unit decreases a little at the beginning ($20) and then after period 9 an additional decrease is observed, of $80 per unit regarding its energy cost. When the savings are 0.3 (Fig. 15) and 0.5 (Fig. 16), the energy costs of per unit of manufactured product from period 9 decrease by $1,800 and $3,000, respectively.

Figure 13 Source: The authors

Figure 14 Source: The authors

Figure 15 Source: The authors

Figure 16 Source: The authors

These variations in the energy cost factor of producing a unit can be taken by the company as a basis for its energy saving decisions.

Evaluating the behavior of waste (Fig. 17), it can be observed that variations are presented that are coherent with the quantity of units that contain each of the production orders. In addition, as time passes there is a slight tendency of growth.

Figure 17 Source: The authors

This increase is due, in some cases, to the greater generation of waste caused by increases in production levels, inefficiencies in the production process, efficiency losses in the use of some waste, or the generation of lower quality waste, limting its use. However, the percentages of waste generation are below 1%. Furthermore, the use of waste also has a slight upward trend, which may be due to a more efficient process or the generation of greater volumes of waste.

Another interesting item to evaluate is the green income (Fig. 18), it is evident that the monthly income of this is estimated at $10,670,000. However, the company can strengthen its policies and actions to use this waste in a better way, taking into account that the recovery rate is at 0.7.

Figure 18 Source: The authors

A systemic vision of the company allows for an understanding of the systemic behavior of the organization’s key aspects, for example, how its decisions can impact on other components within the organization, especially those that are subtle and not easily perceived. Furthermore, the effects can accumulate over time and when they are detected it may be too late to take action to correct the problem.

A four-dimensional model was built for a company, based on the fundamental characteristics of the production process, incorporating elements of business sustainability (environmental, economic and social dimensions) and quantitative modeling. The model was integrated by two large modules which were designated as the manufacturing module and the sustainability module. The first covered the physical and economic component of the production process and the second was divided into sub-modules related to energy consumption, green income, and human talent management. Reference was made to environmental, economic and social indicators, where at least one indicator of the triad was incorporated. Based on the model, some variables of interest were analyzed, such as the storage of finished products, the energy consumed, and the generation of solid waste.

The company incorporates the just-in-time concept into its management, however, when evaluating its policy regarding the handling of inventories, in particular of finished products, as it was found that they accumulate slowly over time. This requires the company to make an assessment of storage costs and opportunity costs against the optimal quantities of inventory that could actually be maintained to ensure the continuity of the production process. Similarly, redefining their policies regarding the consignment of products for their main customers will streamline the movement of these stored products.

Another interesting aspect was related to energy consumption. While measures are not implemented in the technology energy saving factor (equal to 0), this will accumulate over time in direct proportion to the levels of production and inversely to the levels of efficiency and productivity. When a technology energy saving factor equal to 0.3 was established, it was observed that the slope changes to a lower value after period 12. With a technology saving factor of 0.5, the value of the slope decreased from period 9 onwards. Regarding the cost of energy per unit of production, it remained constant when the technology energy saving factor is zero. When the savings were 0.3 and 0.5, the energy costs per unit of manufactured product decreased by $1,600 and $3,000, respectively, from period 9.

With regards to waste generation, in this case, of solid waste; it was determined that its growth is mostly due to increases in production levels, inefficiencies in the production process, efficiency losses in the use of some waste, and the generation of lower quality waste with a limited use.

Finally, since it was structured under a global and systematic scheme of operation and business organization, the developed model and its corresponding methodology forms a basis for its application to other companies of lesser or greater complexity.