**1. Introduction**

Reinforcing bars (rebars) represent a widely used component of reinforced concrete structures in construction projects that significantly influence the project cost and structural stability [1]. To reduce the loss rate, rebar fabrication techniques have been changed from the field to the plant. To avoid delivery delays, the processing time and loss rate in a rebar fabrication plant's production process must be estimated. However, the majority of research that is currently available on the fabrication of rebars has been concentrated on the necessary length and cutting processes of rebars, such as standardizing the length and shape of the rebar to reduce the loss rate, or planning the cutting of raw steel imported to the rebar fabrication plant [2–5]. Although the existing methods, such as an optimization algorithm with an NP-hard problem [6,7], can decrease the loss rates in rebar fabrication plants, the production plan cannot be optimized because such methods do not consider the actual scenario of rebar fabrication plants that perform simultaneous deliveries to multiple sites. For this reason, the goal of this study was to create a simulation model that takes into account the variables that affect work efficiency (such as the quantity of simultaneous cutting and bending operations, and the amount of time needed for cutting and bending) in scenarios involving the simultaneous delivery of rebars to various sites. Through risk processing, the rebar loss rate and processing time for the volume to be delivered were made clear. Even when the production volume from various sites increases, the proposed model can assist in creating an ideal production plan for situations involving numerous sites and varieties of raw steel.

**Citation:** Hong, E.; Yi, J.-S.; Son, J.; Hong, M.; Jang, Y. Rebar Fabrication Plan to Enhance Production Efficiency for Simultaneous Multiple Projects. *Appl. Sci.* **2022**, *12*, 9183. https://doi.org/10.3390/app12189183

Academic Editors: Albert P. C. Chan, Srinath Perera, Dilanthi Amaratunga, Makarand Hastak, Patrizia Lombardi, Sepani Senaratne, Xiaohua Jin and Anil Sawhney

Received: 10 August 2022 Accepted: 7 September 2022 Published: 13 September 2022

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**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

#### **2. Materials and Methods**

#### *2.1. Literature Review*

The existing research on processing plant optimization may be broken down into two groups (Table 1): studies concentrating on timely production management and import systems of processed rebar for rebar building, and those on algorithms to decrease the loss rate.

Many researchers have performed case studies, simulation studies, and algorithmbased studies to optimize rebar fabrication plans or minimize the cost and material waste [1,2,4–6,8–10]. Other researchers attempted to enhance production plans by using simulation-based decision support systems based on rebar specifications [11]. Polat et al. (2007) used a simulation-model-based system to establish a decision support system that recommended lot sizes (large or small), scheduling strategies (optimistic, neutral, or pessimistic), and buffer sizes (large, medium, or small) considering project conditions. This system generated savings of 4.8% in just-in-case scenarios over just-in-time scenarios.

When a rebar fabrication plant must simultaneously process different types of rebars at multiple sites, a certain number of site combinations can be prioritized based on the experience and intuition of the planners. However, given the wide range of rebar types, the labor capacity and expertise may not be adequate. To identify the optimal plan to enhance productivity, various scenarios can be tested using simulation models.

## *2.2. Modeling with DES*

The importance of the rebar type and site-specific combination affects how a rebar fabrication plant's production system evolves over time. To simulate a rebar production process that changes in terms of the productivity of intricate production systems, including numerous delivery combinations with a finite length, discrete-event simulation is an appropriate method. The DES model involves the operation of a system as a discrete sequence of events in time [12,13]. Each event occurs at a particular instant in time and marks a change of state in the system. DES has been used as an effective approach to better absorb complex interactions and uncertainties in construction operations [8,14]. Therefore, in this study, DES modeling was used to develop the best production schedule for rebar fabrication plants.

AnyLogic is a Java-based simulation program that may be used to assess different simulation-related research approaches [15]. Using the building blocks from AnyLogic's process modeling library, a production process simulation model of a rebar fabrication plant was created for this study. By testing different configurations related to the number of sites and raw steel ratio for each length, the developed model was used to reduce the loss rate. To further improve the production plan for the rebar fabrication plant, the processing time was also examined.

DESs were created based on the process depicted in Figure 1 in order to establish simulation models for rebar production plants and determine the optimization methods to lower the loss rates through various site-specific combinations and lengthwise cylindrical import rates. There are four stages to the modeling process. First, in the goal-setting stage, we identify the issues that arise in real-world settings, describe these issues, set goals, and create a study strategy. Second, the operating procedure and current state of the rebar fabrication plant are identified. Third, in order to simulate real-world systems, we gather multiple data points in operations and management during the model design process [16]. Fourth, we visit a real rebar fabrication plant to observe the rebar production process and gather data from each process to assess how well the current system is working. The goal of this study is to reduce the loss rate of the rebar; therefore, we construct a model by simplifying the systems that have an impact on that rate. We next test the model's viability to make sure it accurately captures the real system.


**Table 1.** Existing studies on rebar fabrication management and loss rate minimization.

**Figure 1.** Simulation modeling process flow (Reprinted/adapted with permission from Ref. [17].

#### **3. Problem Definition**

The three steps that make up the rebar production process are shown in Figure 2: (1) importing, (2) cutting, and (3) bending. In the rebar fabrication plant, the required length and shape are calculated according to the strength and diameter of the rebar through design drawings. The received raw steel is processed according to the preceding process (Figure 2), the quality of the processed rebar is checked, and it is then shipped to individual sites. Although this process is straightforward, the loss rate is challenging to minimize because several variables associated with the (1) raw steel, (2) machine, (3) rebar shape, and (4) hoist must be considered. Additionally, we first set the variables that have a decisive effect on reducing the loss rate and necessary time. Firstly, the reason why time is considered the most important among these is that the model built is based on a discrete-event simulation. Secondly, considering the priority, time-related variables were set as major variables.

**Figure 2.** Processing system for rebar fabrication.

Imported raw steel is typically 8 m or 10 m long. With the increasing complexity of construction projects, the required lengths of the rebars at sites vary. The steel that is left over after fabrication is regarded as waste, which raises the project's loss rate or reduces the amount of raw materials accessible for other projects. As a result, plants frequently produce rebar in accordance with requests from several projects at once to reduce the loss rate.

As indicated in Table 2, rebar fabrication involves various types of machines for (1) transporting, (2) cutting, and (3) bending. The cutting machine typically cuts 18 or 24 rebars with a 10 mm diameter at once, or 13 or 21 rebars with a 13 mm diameter at once. There may be a slight delay because the bending machine normally bends five to nine rebars with a diameter of 10 mm, and three to seven rebars with a diameter of 13 mm at a time. Third, the rebar shapes to be fabricated vary across projects, which changes the machine capacities. For instance, the diameter of the raw steel affects how many rebars are produced simultaneously. Finally, depending on the transportation site and rebar shape, the hoist's maximum capacity fluctuates during the rebar transportation operation.

Therefore, by combining numerous locations to gather and process various types of rebars at once, a production plan must be designed that can decrease the loss rate that happens while processing raw steel with a limited length. This framework can also help ensure rebar quality. Notably, no specific standard exists for processing rebars to be delivered to multiple sites simultaneously. The processing of rebars typically relies on personnel experience. In such scenarios, the loss rate cannot be effectively minimized. In order to determine the loss rate, necessary processing time, and ideal production plans, a simulation model was created in this study based on the basic rebar fabrication process.


**Table 2.** Rebar fabrication machine.

#### **4. Modeling Simulation of the Rebar Production Plan**

*4.1. Model Overview*

When designing a simulation model, it is very difficult to consider all the variables that explain the phenomenon; some variables that have a major influence on the phenomenon can be established and disestablished.

The model construction involves three steps. First, in order to reduce the loss rate and necessary time, it is necessary to identify the critical parameters: Following the importation of raw steel from the steel mill and the delivery to the plant, three factors must be considered: (1) site combination, (2) rebar type (the strength, diameter, length, and the form of rebar sent to the sites for actual building activity), and (3) machines (hoists, cutters, and benders appropriate for specific sites and rebars). Second, the raw steel is cut, and the leftover length is put to use again. The amount of rebars that each cutter can cut at once is shown by how the rebars are cut. The proposed approach was built to utilize the most cutting-edge resources possible. Reusing the rebars in this situation is crucial to lowering the loss rate. If the length of the rebar after it has been cut exceeds the length necessary for the type of rebar required at the site, it must be processed into a rebar with a reduced length. The loss rate in this process varies depending on the priority of each rebar type. The third step involves bending the cut rebar. Rebars of various shapes that must be bent are configured to pass through the bender.

By reflecting the abovementioned rebar machining process, an algorithm was established to enable the delivery of rebars to multiple sites simultaneously. To realistically reflect the rebar fabrication plant in the simulation model, the working schedule of an actual plant was used. The operating time of the machine was reflected in the model. In general, rebar fabrication plants operate night shifts during the week for order fulfillment. The plants operate until 6 p.m. on Saturdays and do not operate on Sundays. The simulation model was configured such that the machine was operated during working hours and not operated during breaks. The execution process of the DES model for the rebar production plan is shown in Figure 3.

Because the actual rebar production plant receives orders from and processes orders for up to four locations concurrently, four sites were specified as the maximum number of sites to which orders must be simultaneously supplied in the simulation model. It was also believed that 16 different types of rebars could be handled (eight types of SHD10 and eight types of SHD13, commonly used for apartment slabs and walls at each site, respectively).

**Figure 3.** Process flow of the algorithm reflecting the rebar production process.
