## 1 Introduction  
In the modern era of big data, the demand for higher data rates, low latency, and reliable communication is increasing daily [1]. In the past few years, the number of users is increasing drastically as mobile network communication evolved from first-generation (IG) to fifth-generation (5G) [2]. 1G supported voice calls only, 2G kept message services while 3G had internet support. 4G grew in the 2010s and supported mobile broadband (MBB). In the 2020s, 5G evolved and offered mobile broadband (eMBB), ultra-reliable low latency (URLLC), and massive machine-type communication (mMTC) services. Nowadays, the sixth generation (6G) is developing and offers intelligence and sensing technologies. These technologies require more bandwidth and data rates. Figure 1, shows the evolution of mobile communication from 2G to 6G.  
Figure 1: Evolution of mobile network from 2G to 6G.  
Moreover, the use of mobile networks in the industry has also increased, and to fulfill the stringent requirements of industry 5.0 and beyond, the research to deploy next-generation (6G) networks has started. Industry 5.0 is based on human-centric solutions and supports mass customization. Figure 2 shows the industrial evolution. The primary requirements for industry 5.0 are high energy efficiency (EE), low latency, high spectral efficiency (SE), and high throughput [3]. The solution to fulfill all these requirements is deploying 6G in industry 5.0. However, the deployment of 6G in the industry is quite challenging. Due to non-line of sight (NLOS), the EE and throughput of the network decrease. NLOS also gives rise to multi-path fading, attenuation, and interference due to reflection and refraction. To overcome this problem, reconfigurable intelligent surface (RIS) is the primary solution [4]. RIS reduces attenuation and improves network performance [5].  
RIS consists of electromagnetic (EM) materials and possesses EM properties. These are thin sheets deployed on the buildings, walls, and machines. The EM nature of the RIS helps to monitor the medium of the whole network and the mode of operation of RIS, which is full-duplex [6]. The deployment of RIS is also cost-effective because it is a passive device. PIN diode controls the phase shift (\(\Theta\)) of RIS [7] and helps to achieve a particular phase by switching function [8].  
When the state of the PIN diode is low the incoming energy (\(h\upsilon\)) passes through it due to its installation on the frequency selective surface (FSS). Whereas, when the state of the diode is high most of \(h\upsilon\) is reflected. A RIS-assisted network base station (BS) transmits a signal to RIS and RIS improves the characteristics of the incoming signal which helps in improving the overall performance of the network [9, 10, 11, 12, 13].  
Inspired by the numerous benefits of RIS-assisted networks, we formulate an optimization problem to enhance EE, SE, throughput and minimize the latency of the network in an industry 5.0 scenario. We propose a novel algorithm to solve the optimization problem. Following are the primary contributions of this article.  
1. We formulate an optimization problem in the RIS-assisted wireless network in the industry 5.0 scenario.
2. We propose a novel algorithm to solve the optimization problem and evaluate EE, SE, throughput, and latency.
3. We allocate resources and evaluate the channel mode.
4. We compare the performance of the proposed algorithm with others.