The term “manual assembly” refers to a process in which human operators use their innate dexterity, aptitude, and judgment to combine pre-existing parts to create a finished product or a unit of a finished product. According to Richardson et al. [1], the activity of manual assembly is a type of spatial problem-solving that requires workers to construct a mental model in order to interpret and engage with spatial input. Work instructions, their presentation, and the worker’s interaction with them are extremely important in manual assembly operations [2,3,4,5]. Work instructions must be clear and unambiguous about which parts to utilize and how they should be built in order to optimize the operators’ mental abilities [4]. It is generally accepted that assembly instructions must be provided in a way that allows everyone to read them and successfully complete the assembly [6]. In this manner, work instructions can help reduce the mental load on the operators, in particular by simplifying the complexity of the tasks. Today, most manual assembly instructions are provided digitally, on a computer display, and include text and visual content [2,3,4,5]. However, Mattsson et al. [7] believed that instructions should be highly perceptual, which necessitates providing the operator with more sophisticated and timely sensory inputs. Using three-dimensional models in work instructions improves their realism, accuracy, and legibility in depicting the assembly process. Perspectives and basic assembly guidelines might be included in these model-based instructions (MBI) [8,9].

The assembly process is crucial to manufacturing because it guarantees that the final product meets the necessary quality standards. Several factors, such as flexibility, the variety of products, the volume of production, and productivity, are considered by engineers when selecting an appropriate assembly system [6,10]. Despite the lower productivity and production volume in manual assembly systems compared with automatic assembly systems, manual systems have an increased flexibility and variety of products. Worker productivity is a measure of the output or results achieved by an individual worker or a group of workers within a specific time. Figure 1 illustrates the impact of assembly system automation on these factors. Although industrial robots contribute greatly to the automation of manufacturing systems, including assembly systems, the complexity and diversity of the product still represent significant challenges in manufacturing; therefore, manual work remains a viable and irreplaceable alternative [6,11]. These manufacturing fields include electronics, aerospace, automotive, combustion engine assembly, and industrial machinery and equipment [12,13]. Manual assembly requires the precise execution of a number of steps in order to yield a finished product of the requisite quality. Torabi et al. [14] discussed the common human errors in the design, installation, and operation of variable air volume air handling unit systems. They identified that many types of faults can occur, including design, assembly, manufacturing, incorrect operation, maintenance, software, and operator’s faults, and the mistakes that humans directly cause may be referred to as errors. Park et al. [15] have designed a software tool called Foolproof Joint that simplifies the assembly of laser-cut 3D models to reduce assembly errors by modifying finger joint patterns. They [16] developed an intelligent detection approach to detect human errors in the maintenance and assembly of components of a nuclear power plant using artificial intelligence. Wang et al. [17] investigated the vibration characteristics of the spindle system and discovered that the vibrations were caused by assembly errors.

Furthermore, Miao et al. [18] and Wang et al. [19] mentioned that supporting bearing assembly errors have a significant impact on bearing operating performance and spindle vibration characteristics. Human error (HE) is one of the most common causes of accidents in many industries. Previous studies indicate that HE contributes to 30–90% of all accidents in work environments despite strict safety procedures in those industries [20]. Common types of human errors (HEs) in assembly processes include unsecured links, missing parts, improper part installation, the inadequate application of force to fasteners, breakage during assembly, and contamination by foreign object debris [21,22]. Inadequate cognitive and physical ergonomics have also been found to impact product quality and increase the frequency of errors [11,23].

Moreover, there are many other kinds of human errors that are capable of occurring throughout the assembly processes. Here are a few common examples:

(1)

Omission errors: These occur when a step or task in the assembly process is missed or skipped over entirely. For example, a worker might forget to install a specific component or tighten a screw;

(2)

Commission errors: Commission errors occur when a worker does an action incorrectly, such as installing a part backward or using the wrong tool;

(3)

Transposition errors: These errors occur when two similar-looking parts or components are confused with each other. For example, two screws of different lengths might look similar, and a worker might accidentally use the wrong one;

(4)

Timing errors: Timing errors occur when a worker completes tasks in the wrong order or sequence, which can cause problems down the line. For example, a worker might install a part before another part that should have gone in first;

(5)

Procedural errors: These errors occur when workers do not follow the correct procedures or instructions for a task. This could be due to a lack of training or understanding of the instructions;

(6)

Communication errors: Communication errors can occur when workers do not communicate effectively with each other or when instructions are unclear or misunderstood;

(7)

Fatigue-related errors: Errors can also occur due to factors such as fatigue or stress, affecting a worker’s attention and decision-making abilities.

It is essential to remember that these errors can frequently be connected to one another and exacerbate one another, which might result in more severe issues throughout the assembly processes. Therefore, it is important to identify these errors and know the factors causing them as early as possible to prevent more significant issues.

With the advent of Industry 4.0, increased product customization will occur in highly flexible production settings [6]. As a result of this widespread personalization, manufacturing is likely to become more complicated, possibly calling for more highly trained employees [23]. Reducing HEs in this situation depends critically on a well-optimized work system. A well-optimized work system refers to an effective arrangement of people, processes, resources, and technology that maximizes productivity, quality, and overall performance. It is designed to streamline workflows and reduce human errors to achieve desired outcomes. Identifying the aspects and factors influencing operator performance is crucial for optimizing assembly processes and minimizing errors. Many factors directly or indirectly influence the assemblers’ errors during the manual assembling processes. Identifying the most critical factors needs much research in the field, which is time-consuming and expensive; moreover, some previous studies focused on defining and identifying some of these factors and did not address identifying which factors are the most influential for these errors.

2. Factors Affecting Human Errors in Manual Assembly Processes