Abstract
Many companies in the industrial sector are currently facing massive changes in order to optimize processes and enable new customer demands (e. g. mass customization of products). Often, these changes are related to a modernization of existing infrastructure to enable cyber-physical systems and smart factories (so called Industry 4.0). These structural changes have effects on business processes and business models. Consequently, the factory workers need to adapt to the changing infrastructure and therefore, it is necessary to analyze how factory workers can be supported during their day-to-day work in the changed environment. Thus, an important aspect is the analysis of human computer interaction interfaces which aim at assisting factory workers. One promising human computer interface solution between cyber-physical systems and factory workers are smart glasses, as this technology is suited for assisting humans hands-free. Since prior research on application scenarios of smart glasses in the industrial sector is limited, the aim of our research is to identify relevant application scenarios. Therefore, we conducted a qualitative, explorative study by interviewing 21 domain experts. Based on this, we derived 15 application scenarios which can be used by both, research and practice, to develop and evaluate new human computer interaction interfaces for industrial applications.
1 Introduction
Currently, increasing efforts to modernize existing infrastructure in the industrial sector can be seen [11]. This trend, which is known under the term Industry 4.0, aims at optimizing production processes by increasing the data collection, data exchange and use of new manufacturing technologies [22, 26]. Reasons for this are e. g. the demand of users for customization of products (batch size of one) or efforts to optimize manufacturing processes by applying predictive maintenance methods or just-in-time production [11]. These changing circumstances also affect factory workers as they need to adapt to the changed manufacturing technologies and work environment [8, 27]. Consequently, it needs to be analyzed how workers in the industrial sector can be supported to interact with these changed technologies and how existing human computer interaction interfaces and assistance systems need to be adjusted to profit from and support the modernized industrial infrastructure.
One promising human computer interface solution between cyber-physical systems and factory workers are wearable computers and especially smart glasses [28, 30] as they are able to display information proactively and enable the user to interact with them hands-free during their work [3]. Even though wearable technology has been explored for more than 50 years [31], marketable and industrial-suited wearable computers are available only now [20]. Smart glasses and other wearable computers can be used hands-free and are portable while operational because of its capability to communicate with other information systems using wireless communication technology (e. g. WiFi or Bluetooth) [4, 25]. Because of this, they are suited to assist workers in the industrial sector and it is expected that smart glasses are able to optimize industrial processes:
“We want to offer workers the possibility to work hands-free [using smart glasses]. Thereby, we expect improvements in efficiency.”
(Expert 19)
Prior research confirms that smart glasses are suited for being used in some specific situations (including logistics and the health sector; [21]). However, a practice-oriented analysis of application scenarios of smart glasses in the current state of the industrial sector is missing. In this paper, we present the results of a qualitative empirical study on the use of smart glasses in the industrial sector. Therefore, we conducted interviews with domain experts to get practice-oriented insights about potential application scenarios.
Accordingly, we address the following research question in this paper:
In which application scenarios are smart glasses useful for supporting workers in the industrial sector?
To answer this research question, this article is structured as follows: First, we present definitions of important basic terms like wearable computers and smart glasses. Thereby, we also outline related research of using smart glasses in industries. Afterwards, we describe the research methodology of our qualitative empirical study. Following this methodology, we subsequently show the findings of our study by describing identified application scenarios for using smart glasses in the industrial sector. Finally, we discuss our findings and highlight future research directions.
2 Basics and Related Literature
Smart glasses can be defined as wearable computers in the shape of glasses consisting of a glasses frame and an integrated head-mounted display [13]. As such, they are worn on the user’s body and are therefore available to the user independently of a specific location or time [6]. They are always turned on and always reachable by the user (e. g. on the user’s head or wrist) which enables them to be used immediately and simultaneously to other activities [6, 10, 25]. This give wearable computers the possibility to proactively start interactions with the user, e. g. by displaying relevant information in the field of vision on the display of smart glasses without the user’s action [3].
Furthermore, wearable computers can be seen as an enhancement of mobile devices (like smartphones and tablets) [10], since they share mostly the same hardware components [19, 23]: For instance, they include an integrated processor, a power supply and wireless communication technologies [6]. In order to enable interaction with the user, input and output capabilities are essential for wearable computers. Thus, state of the art smart glasses have built-in head-mounted displays which are located in the user’s field of vision [13], microphones to enable spoken text input [5], speakers or headphones for audio output and either a touchpad or buttons for touch input. Furthermore, smart glasses usually have multiple integrated sensors like an eye tracker or a gyroscope. In many cases (e. g. Google Glass) also cameras are integrated to enable visual input. Even though as of today smart glasses, other wearable computers and mobile devices consist of similar hardware components, smart glasses have the advantage of enabling a hands-free and incidental use, i. e. the user is able to interact with the device without the need of holding it in his hands [14].
To summarize, an overview of relevant characteristics of up to date smart glasses which are relevant for this study is shown in Table 1.
Selected characteristics of smart glasses.
| Characteristics | Smart glasses | |
|---|---|---|
| Input capabilities | Voice input with speech recognition | Camera input |
| Sensor data (e. g. eye tracker or gyroscope) |
Touch input (limited) |
|
| Output capabilities | Head-mounted display | Audio output (speaker or headphone) |
| Type of use | Active | Incidental |
Prior research papers about wearable computers have been published more than 50 years ago [15, 31]. However, research on application scenarios of smart glasses in industrial contexts is limited. In the last years, some scientific articles about using smart glasses in few specific exemplary application scenarios (e. g. in manufacturing or logistics) have been published. For instance, Paelke [21] presented initial experiences with an augmented reality system which can be used for supporting workers in an Industry 4.0 environment. Another recent example is a prototype, presented by Quint / Loch [24], which can be used for documentation purposes in manufacturing. The presented prototype was used to record videos from manufacturing tasks. An example of using smart glasses in logistics is presented by Guo et al. [9]: In their paper, the authors analyze different picking methods including pick-by-vision using head-up-displays and show that smart glasses can improve the picking process. Furthermore, Hobert et al. [10] derived application scenarios for augmented reality learning in industrial production facilities. Even though selected application scenarios have been analyzed in first research papers, an overview of application scenarios for smart glasses which is applicable for both – research and practice – is missing.
3 Methodology
As the existing literature about using state-of-the-art wearable computers (especially smart glasses) in industries is limited (see section 2), we choose to collect explorative, empirical data by conducting interviews with domain experts in order to deduce application scenarios and thereby answer our research question. Thus, we aimed at getting new insights about potential use cases in the industrial sector.
As displayed in Figure 1, the sample of domain experts was drawn in two steps: First, during an industrial fair in April 2015, potential interviewees were asked to participate in the interview study. To increase the sample size, in a second step further interview requests were sent out via e-mail to German and Austrian companies, which are using wearable technology, are providing wearable solutions for the industrial sector or are considering the use of these technologies in an industrial context. In total 21 interviewees participated in the study (see Table 2) which corresponds to an acceptance rate of 37.5 %. We covered a broad range of different industries like the automotive and manufacturing industry as well as companies from the industrial automation sector and suppliers of industrial-suited wearable computing technology. With this sample, we intended to select an adequate cross section of the industrial sector in order to identify application scenarios of smart glasses.
Characteristics of the sample.
| Expert | Function | Length of recording |
|---|---|---|
| Exp1 | IT Product Manager | 35 min |
| Exp2 | Chief Executive Officer | 39 min |
| Exp3 | Chief Executive Officer | 34 min |
| Exp4 | Chief Technology Officer | 36 min |
| Exp5 | Chief Executive Officer | 51 min |
| Exp6 | Chief Executive Officer | 65 min |
| Exp7 | Chief Executive Officer | –* |
| Exp8 | IT Solution Architect | 68 min |
| Exp9 | Head of process management | 50 min |
| Exp10 | Training Supervisor | 49 min |
| Exp11 | Field Representative | 33 min |
| Exp12 | IT Senior Consultant | –* |
| Exp13 | Chief Executive Officer | 33 min |
| Exp14 | Chief Executive Officer | 45 min |
| Exp15 | R&D Employee | 33 min |
| Exp16 | Manufacturing IT Employee | 54 min |
| Exp17 | Chief Technology Officer | 38 min |
| Exp18 | Logistics Consultant | 36 min |
| Exp19 | System Analyst | 25 min |
| Exp20 | Senior Manager Corporate Production | 42 min |
| Exp21 | IT Business Analyst | 34 min |
Research Design.
In order to focus on application scenarios in the industrial sector, but at the same time to leave the interviewees enough room to express own ideas, we conducted semi-structured interviews using a prepared interview guideline [18]. Based on this, all interviews were conducted via phone between July and December 2015 and lasted between 25 and 68 minutes. If permitted, the interviews were recorded on tape to allow further in-depth analysis. In total, 19 interviews were recorded with a total length of approx. 13.3 hours.
To analyze the interviews, we applied the structured content analysis approach [16]. Therefore, we first anonymized and transcribed the recordings. Afterwards, all transcriptions were coded using the software MAXQDA. Based on this, we derived potential use cases for smart glasses in the industrial sector as described in the following chapter. For publishing the results, relevant quotations were translated into English using constant contextual comparison [29].
4 Findings
As a result of the conducted interviews, we identified use cases for smart glasses in industrial business processes of manufacturing, maintenance, logistics and quality control. Furthermore, our interviewees stated, that smart glasses are suited for supporting cross-sectional tasks of employee training and remote support which can take place in all business processes. Table 3 depicts an overview of the identified application scenarios which are described in the following subsections.
Overview of identified application scenarios.
| Application scenarios | No. Exp. | ||
|---|---|---|---|
| Employee training | U1.1 | Incorporation into practical workflows | 7 |
| U1.2 | Supervision of learners executing workflows | 3 | |
| U1.3 | Demonstration of practical knowledge in classroom training courses | 2 | |
| Manufacturing | U2.1 | Process guiding | 6 |
| U2.2a | Provision of background information | 4 | |
| U2.2b | Notification about anomalies | 3 | |
| U2.3 | Provision of feedback | 1 | |
| Quality Control | U3.1 | Process guiding | 8 |
| U3.2 | Documentation | 3 | |
| Maintenance | U4.1a | Provision of real-time sensor data | 6 |
| U4.1b | Notification of upcoming maintenance task | 4 | |
| U4.2 | Process guiding | 6 | |
| Logistics | U5.1 | Supporting picking | 12 |
| U5.2 | Reporting defect items | 2 | |
| Support | U6 | Remote Support | 13 |
4.1 Employee Training
In the industrial sector, employee training usually takes place either in the skill adoption phase, when newly hired employees get trained after recruitment [7], or in the day-to-day work when knowledge needs to be refreshed or extended (e. g. further information about workflows is needed). Even though learning in formal settings (e. g. classroom teaching) is applied in industries, it is often required to perform regular tasks to train workflows (so-called learning on the job [32]).
Several interviewed experts (e. g. Exp3, Exp9 and Exp21) indicated that in the initial skill adoption phase the use of smart glasses can support the incorporation of employees into practical workflows (see Table 4). In particular, smart glasses can be used to guide employees step-by-step through workflows by displaying appropriate learning content (e. g. operating instructions) including detailed background knowledge. As smart glasses can be used to display information hands-free, the workers are able to focus on the execution of the workflow while learning content is presented. By applying knowledge at the workplace, procedural knowledge can be trained.
Use cases for employee training (1 / 3).
| Use Cases | Exemplary Quotations |
|---|---|
|
U1.1
Incorporation into practical workflows |
“The time consumption of [the initial-skill adoption phase] has been reduced, because we give smart glasses [to the learners]. We show individual production steps on the display.” Exp9 |
| “During training mode, the apprentices do not only see production steps, but also additional information how to execute them […]. This is additional information which is usually only available in paper based folders. Now we can show [the information] to the learners directly.” Exp9 |
In addition to that, two experts (Exp10 and Exp20) described a use case for supporting the supervision of learners through smart glasses (see Table 5): While the supervision of learners in formal settings (like in classroom teaching) is usually not a problem, in the apprenticeship learners often apply their knowledge simultaneously at their own workplace. Therefore, it is usually harder for the instructor to supervise all learners at different locations at the same time. Exp10 and Exp20 proposed that trainees should be equipped with smart glasses to enable the instructor to support the trainees remotely by establish a video call. As camera equipped smart glasses are able to record the user’s field of vision, the interviewees expect that instructors are therefore able to support the learning as good as in person. This use case could also be transferred to long distance learning, when learners are spread across different factories or countries but supervised by a single trainer, as stated by Exp6.
Use cases for employee training (2 / 3).
| Use Cases | Exemplary Quotations |
|---|---|
|
U1.2
Supervision of learners executing workflows |
“If I am sitting in my office and the trainee, who is working in the factory, has a question, he could call me immediately using his smart glasses and share his field of vision. Then I could help him virtually (…). This would reduce our workload.” Exp10 |
| “[…] a live class room with the possibility to […] coach learners during the instruction.” Exp6 |
Furthermore, even in classroom training courses with larger groups of learners, smart glasses can enhance employee training: By using smart glasses, trainers have the possibility to demonstrate practical knowledge to learners by recording the field of vision and streaming it live to a data projector. For instance, Exp10 and Exp21 look forward to present their practical explanations (e. g. how to equip an electrical cabinet, Exp10) simultaneously to a group of up to 30 apprentices in the classroom. At the moment trainers don’t have this opportunity and need to split the class into smaller groups (e. g. up to 5 learners) and explain the practical knowledge separately. Thus, demonstrating practical knowledge is very time-consuming at the moment. Table 6 depicts exemplary quotations of interviewees describing this use case.
Use cases for employee training (3 / 3).
| Use Cases | Exemplary Quotations |
|---|---|
|
U1.3
Demonstration of practical knowledge in classroom training courses |
“[…] to use smart glasses for sharing my field of vision, because I have training courses and I often have the problem [of demonstrating things]. I always need to explain it in groups of three. For each explanation I need five minutes. If I need to do this 20 times, it sums up to 100 minutes. I really could use that time more efficiently.” Exp10 |
| “But now, smart glasses give us the opportunity to actually record exactly what you need to communicate and some of these trainings that happen in person do not necessarily show angles that you could show. For example, if someone is showing how an object looks like and there are 15 people around, then not everyone has the same view. With smart glasses you can make sure that everyone in the session has the same view and right input you want them to see.” Exp21 |
4.2 Manufacturing
Manufacturing processes are essential for the industrial sector, as they are most important for the value creation (i. e. creation of products). Even today many manufacturing processes need to be executed by factory workers. In order to become more efficient and to support their employees, more than one third of our interviewed domain experts mentioned use cases for smart glasses in manufacturing.
In order to ensure, that factory employees work through the whole workflow and do not miss any important step of the process, the interviewees stated (e. g. Exp3, Exp13 and Exp19; see Table 7), that smart glasses should provide process guiding to the employees. This means that smart glasses should show the individual production steps. In contrast to step-by-step tutorials (see U1.1), in this case the displayed content should be limited to necessary information (e. g. “Execute task1”) and should not be overloaded with learning content. An information overload could distract the workers and reduce their efficiency. In addition to the presentation of process steps, Exp19 mentioned that checklists could be integrated in the process guiding as well. By doing this, the workers should be able to confirm the execution of process steps and the processing of the workflow in the correct order could be ensured.
Use cases in manufacturing (1 / 4).
| Use Cases | Exemplary Quotations |
|---|---|
|
U2.1
Process guiding |
“I often have the challenge to work hands-free, but at the same time I need access to the process and the individual steps.” Exp3 |
| “In production I often need process guiding.” Exp3 | |
| “This is relevant for the confirmation of tasks. […] An employee inputs that a task has been accomplished.” Exp19 |
In addition to process guiding, the provision of additional information was mentioned as a relevant scenario for smart glasses. In this case, two use cases can be distinguished:
First, the experts (e. g. Exp8, Exp13 and Exp16; see Table 8) determined the need for background information (like CAD drawings or reference pictures) which are often required by workers. This is especially relevant when complex manufacturing tasks need to be executed. Even though this information is available today, it is usually only available as paper based hard copies (Exp13). As manufacturing employees usually need that information hands-free while executing tasks, they currently cannot access it easily. Therefore, the experts proposed to display the relevant information on smart glasses, so that workers can access it immediately. However, it needs to be verified that the screen space and resolution of available smart glasses is sufficient for the presented information. Especially if CAD drawings should be presented, this could be problematic.
Use cases in manufacturing (2 / 4).
| Use Cases | Exemplary Quotations |
|---|---|
|
U2.2a
Provision of background information |
“It is often required that users access further documents […]. These are for example assembly instructions, CAD drawings, everything you can imagine. At the moment these are often pieces of paper.” Exp13 |
| “In the field of manufacturing, you can do target / actual comparisons […]. If a worker stands in front of a workpiece and e. g. has to weld certain welding points […] then you can show a reference image. […] He can check if all welding points are correct. […] He can also see which welding points need to be added.” Exp16 | |
| “I can imagine that – especially for worker assistance – wearables [like smart glasses] are well suited for visualizing things. […] You can get access to information more directly and faster […] You can get connected to data more intensively.” Exp8 |
The second use case concerning the provision of additional information in manufacturing processes is the notification of workers about anomalies in the workflow. According to Exp8 and Exp15, e. g. in the batch production in the car industry the factory workers often have to repeat the same production steps over and over again. However, in rare cases production steps need to be changed, e. g. if extra equipment needs to be mounted. Exp8 proposes that workers should be notified via the display of smart glasses in such cases and detailed information about the adjusted production steps should be shown. An exemplary quotation describing this use case is shown in Table 9.
Use cases in manufacturing (3 / 4).
| Use Cases | Exemplary Quotation |
|---|---|
|
2.2b
Notification about anomalies |
“Another possible scenario is if a rare component arrives […] this gets visualized. […] One example is: There is a vehicle with unusual equipment – extra equipment or something like it – that needs to be installed only once a month. Then nobody is specialized in doing this, because nobody does this task several times a day. To avoid construction errors, you try to prevent errors by notifying workers […] and showing suitable advices.” Exp15 |
Finally, one expert (Exp9; see Table 10) suggested to use smart glasses to give workers instant feedback about their work performance. Especially, if employees are paid by piecework, it is usually in their interest to reach the planned production targets. Thus, by providing instant feedback about the work performance, the employees should be motivated. This use case can be summed up as a minimalistic form of gamification at the workplace.
Use cases in manufacturing (4 / 4).
| Use Cases | Exemplary Quotation |
|---|---|
|
U2.3
Provision of feedback |
“An additional value is the use [of smart glasses] as motivation support. One benefit is a personalized display to motivate employees. We are thinking about displaying additional information: How fast is an employee and how does he perform.” Exp9 |
4.3 Quality Control
After finishing the manufacturing of goods in the industrial sector, usually all produced goods (or in some cases only a random sample) need to be reviewed in order to detect errors. These quality control processes often need to be done manually.
During our interviews, eight experts (e. g. Exp3, Exp16 and Exp19; see Table 11) pointed out that smart glasses could be used for process guiding in quality control. However, the interviewees described different forms of process guiding: Exp3 declared that it is sufficient to display the single tasks (without further explanations, e. g. “Executed taskX”) to the employee including the correct order in which these tasks should be executed. Thereby, the employee should be guided step-by-step through the quality control process. Similar to that, Exp16 suggested showing target / actual comparisons to the quality control employees. Exp19 proposed a more sophisticated approach: He stated that augmented reality could be used in order to highlight critical points of the process (e. g. welding lines), which should be analyzed carefully.
Use cases in quality control processes (1 / 2).
| Use Cases | Exemplary Quotations |
|---|---|
|
U3.1
Process guiding |
“[You can use it] in quality control: You need to display, what to check in which order.” Exp3 |
| You can also use it [smart glasses] in quality control: I have a caroche or work piece and I need to do a target / actual comparison. […] Some kind of visual inspection” […] Exp16 | |
| “[…] we would like to do something with augmented reality, e. g. in the cockpit or the engine compartment or the underbody, when the car is jacked up and then it should display which points need to be verified.” Exp19 |
In addition to process guiding, it was proposed that smart glasses should be used for documentation purposes. In many situations the interviewees mentioned that it is required (or desired) that the company is able to document the results of the quality control process (see Table 12). According to Exp15, in such cases it is often sufficient to scan a barcode of checked products and store that information. In contrast to that, other interviewees would like to document the results by taking pictures (Exp18) or by recording the whole quality control process as a video (Exp2). In all cases, the experts explained the benefit of using smart glasses compared to other devices with the possibility of a hands-free use.
Use cases in quality control processes (2 / 2).
| Use Cases | Exemplary Quotations |
|---|---|
|
U3.2
Documentation |
“Some people indeed just want to document […] I, as a quality control employee, need to prove that I did this and that. Therefore, the pure documentation [of my work] is required.” Exp2 |
| “E. g. in a quality inspection of a car, you can use them [smart glasses] to scan a barcode […] and record the result of the inspection in any system.” Exp15 | |
| “[Without smart glasses] it was more complicated to take pictures, because if you found an error […] you need to take a picture with an external camera or scanner, which is scanning documents. All of this could be done with a wearable at the location where the error is detected. Then you can send this information to the QA system.” Exp18 |
4.4 Maintenance
Maintenance processes are essential for the industrial production, as they are needed to ensure that industrial production facilities are available and functional [12]. The importance of maintenance can be seen, as companies spend up to 60 percent of the production costs on service and maintenance [17]. The impact of maintenance is also represented in our interview study: More than 50 percent of our interviewees talked about using smart glasses for maintenance processes.
Many experts (e. g. Exp1, Exp3, and Exp13) emphasized the need to supply sensor data of machineries (e. g. status or health information) to service technicians. Thereby, they highlighted that currently other devices than smart glasses like tablet computers or terminal computers are used for displaying sensor data – however only if this data is already accessible at all. Currently, this method for providing sensor data to employees is problematic in many industrial maintenance processes as “[…] this information should be accessible very fast, without the need of taking off the worker’s gloves or without the need of going to a classical, distant operating panel.” (Exp1).
The need for sensor data can be considered from two different perspectives: First, the experts claimed that real-time sensor data would be useful for service technicians in order to assist them while repairing or maintaining machineries (see Table 13). Besides the overall state of machineries, the real-time values and curve progression of specific sensors are useful for maintenance workers. To assist the workers perfectly, the data should be displayed on smart glasses automatically in a way that they can be accessed hands-free while executing maintenance tasks. Therefore, Exp13 proposed that smart glasses should automatically detect the current machinery and establish a connection to the relevant sensors (e. g. those which shows anomalies).
Use cases in maintenance processes (1 / 3).
| Use Cases | Exemplary Quotations |
|---|---|
|
U4.1a
Provision of real-time sensor data |
“When a service technician is working at a machinery and needs further sensor data […] then this information should be accessible very fast, without the need of taking off the worker’s gloves or without the need of going to a classical, distant operating panel.” Exp1 |
| “The question is: How can I provide information to the user and I think about wearables and specifically about [smart] glasses? […] especially regarding assistance, there you can imagine that you are in a situation where you cannot work properly and the service technician really needs both hands. Then it really makes sense.” Exp8 | |
| “So there is something to repair and it gets displayed on his smart glasses how to fix it and he gets the location of the required component. So he can find the component faster. And he gets provided with information.” Exp13 |
A second use case concerning sensor data mentioned by our interviewees (e. g. Exp1, Exp3 and Exp8; see Table 14) is related to predictive maintenance, i. e. the automatic prediction of faults in the production [1]. Therefore, smart glasses should be used as displays for notifications send out by machineries or monitoring systems: As soon as a machine registers anomalies which could possibly result in an outage or a required maintenance break, a nearby service technician should be notified. In addition to the notification of upcoming maintenance tasks, the smart glasses should also provide relevant sensor data and available timeslots for maintenance breaks. By providing this information to the employees as soon as possible, the interviewees expect to reduce machinery outages and costs.
Use cases in maintenance processes (2 / 3).
| Use Cases | Exemplary Quotations |
|---|---|
|
U4.1b
Notification of upcoming maintenance task based on sensor data |
“We have a machine park with hundreds of thousands of sensors which are located inside of machines, which provide sensor data to our monitoring platform. In our monitoring system, we analyze those data and as soon as certain thresholds are exceeded, we notify machine operators or service technicians on their smart glasses” Exp3 |
| “This is especially relevant regarding equipment condition monitoring and predictive maintenance […] and especially for equipment monitoring or other maintenance scenarios you can certainly imagine that using smart glasses and other wearables have a benefit.” Exp8 |
In addition to sensor information, experts like Exp5 and Exp8 also stated that process guiding with step-by-step instructions – like in manufacturing – would simplify maintenance task. In contrast to manufacturing (see section 4.2), in maintenance it is often not possible to determine the correct solution automatically. Thus, smart glasses should first assist the worker to identify the cause of a problem and let him choose the right solution. Based on this, step-by-step instructions should be displayed for assistance. Exemplary quotations are displayed in Table 15.
Use cases in maintenance processes (3 / 3).
| Use Cases | Exemplary Quotations |
|---|---|
|
U4.2
Process guiding |
“In my opinion, maintenance and repair is the application area in the business context which is really, really fascinating. […] When I am at the correct location, I need to find out: ‘Where is my component?’, ‘Where is my machine?’ and when I found it, I need information what to do. For example, a step-by-step instruction or access to repair instructions or maintenance instructions. […] For example a step-by-step instruction on a smart glass.” Exp5 |
| “I imagine an employee who is looking at a complex system and he got a message that maintenance is required soon. Then this person must either be an expert who is overlooking this, or he needs to be assisted, e. g. by showing recommendations for actions. […] Then we arrive at wearables like smart glasses.” Exp8 |
4.5 Logistics
Logistic processes are relevant in most industrial production companies either when goods need to be transferred to a customer (so called inter logistic) or when components need to be transferred in-house, e. g. when components need to be picked for manufacturing (so called intra logistic; [2]). Even though intra logistic and inter logistic processes differ in companies, all use cases identified by our interviewees in logistics can be considered together as all relevant aspects exist in both, intra and inter logistics. In total, 13 out of 21 interviewees mentioned use cases in logistics.
As already identified in previous literature (see section 2), our interviewees (e. g. Exp6, Exp16 and Exp18; see Table 16) highlighted the use of smart glasses for supporting picking processes. To support such processes in either intra or inter logistics, smart glasses should display the items on the picking list (name of item, quantity and location) and ideally should navigate the employee to the next location. Furthermore, it was said that smart glasses could also be used in this processes for scanning the items to verify that the correct item was picked and to enable tracking. As stated for example by Exp6, using smart glasses in this case could simplify the work and is able to increase the workers efficiency, because the employees are able to work with both hands. Especially when large and heavy items should be picked, the possibility to use both hands was declared as a massive improvement (Exp7). Furthermore, many handheld scanners which are currently being used in companies are rather heavy and unhandy as described by Exp16. By using smart glasses, those handheld devices could be replaced and the picking process could be simplified.
Use cases in logistics (1 / 2).
| Use Cases | Exemplary Quotations |
|---|---|
|
U5.1
Supporting picking |
“The work is usually done using big handheld scanner. These are quite expensive, heavy and buggy. Then one of our departments initiated a pilot project with Google Glass: If you are standing in front of a shelf, you can scan the items and get information about the quantity […] and a picture of the item gets displayed, which should be picked. Then the next step will be displayed: The next shelf where I need to pick an item.” Exp16 |
| “For each task [it] should be displayed: which shelf, which height, which box, which item, which material is required. We display an image from the database and are able to track if the correct item was taken. Then the next task will be displayed. That doesn’t sound much, but it is the complete process and extremely important for a warehouse. These are the core functionalities!” Exp6 | |
| “[The scenario] was to send a picking task to a smart glass – in individual user dialogs. If you think about tasks consisting of five positions, then the employee has to process three dialogues. First, you get asked to go to a specific location, then you should pick the article and scan it with your smart glass to track it in the system.” Exp18 |
In addition to that, it was mentioned by Exp15 and Exp18 that currently the reporting of defects could also be improved by smart glasses. Typically, when an employee discovers faulty items, it is necessary to document the defect by reporting it to the warehouse management system. As said by Exp18, it is often required to attach pictures of the faulty item as well. However, as of today in many cases pickers do not have the possibility to take pictures and instantly attach them to a fault report. Therefore, two of our interviewees proposed to use smart glasses for this as well: Firstly, the worker should be able to take pictures of the defect and secondly, it should be transferred automatically to the warehouse management system. This would speed up the processes of documenting the defect massively, as the picker do not need to fetch a camera, transfer the pictures to a desktop computer and upload it to the warehouse management system. Table 17 displays an exemplary quotation of this application scenario.
Use cases in logistics (2 / 2).
| Use Cases | Exemplary Quotation |
|---|---|
|
U5.2
Reporting defect items |
“My location is this, the defect is that. All this can be reported […] by just taking a picture and by selecting a predefined defect reason via the glasses touchpad. I can enhance and simplify the communication.” Exp18 |
4.6 Remote Support
Finally, remote support was mentioned by our interviewees as a cross-sectional task which could be supported by smart glasses. Our interviewees did not assign this to a single business process mentioned above, but proposed the use of smart glasses for troubleshooting independent of a specific process. Therefore, it can be applied in all of them. Even, when third parties like customers are involved, the use of smart glasses enables potentials as stated by Exp1.
The interviewed experts described potential scenarios in which smart glasses could be used as follows (see Table 18): At the moment in many cases when a local field worker is not able to process a certain task, e. g. in manufacturing or maintenance, an expert needs to be called to solve the problem or provide assistance. However, according to Exp1 in many cases skilled experts are not located at the same industrial plant and therefore need to travel on-site which results in increasing (travelling) costs and longer time durations. This is especially a problem when a whole industrial plant needs to be stopped until a problem is solved. Our interviewees proposed smart glasses as a solution for many cases when advices of remote experts are needed: Local field workers should establish a video call to the remote expert using smart glasses. This enables the local field worker to continue working using his hands and the remote expert is simultaneously able to see the local field worker’s field of vision. Thus, even when the local field worker is not trained enough to solve the problem or execute a certain task on his own, the remote expert is able to support him in real time.
Use case for remote support.
| Use Cases | Exemplary Quotations |
|---|---|
|
U6
Remote Support |
“What we tried once was remote support. One of our customers had a problem that he needs to travel to another country in order to maintain a machinery on-site. Often these are trivial matters. Then the customer tried Google Glass.” Exp1 |
| “The problem is on-site, but the person who can help is far away. Most often the staff is poorly qualified on the one site and an expert on the other site. This is typical field service.” Exp6 | |
| “And we had an application over skype, i. e. video. […] The employee in a fabric hall maybe does not know how to continue and needs an advice from an expert. This expert is able to connect to the employee’s or learner’s [smart] glasses. And then he has the field of vision of the learner or employee. Therefore, he can see what the other is seeing and can give advices.” Exp.10 |
The importance of this use case can be seen, as over 60 percent of our interviewees (13 out of 21) named this scenario. Thus, it is the most often mentioned use case in our study. Table 18 depicts a selection of exemplary quotations concerning remote support.
5 Discussion
Our findings presented in this study imply that smart glasses can be used in many different application areas in the industrial sector. Even though the application scenarios are differentiated by our interviewees and are classified in six different categories in section 4, many application scenarios have commonalities from a technical perspective and are therefore similar to each other: Especially the guidance of workers through processes using step-by-step instructions can be identified in several categories: In manufacturing (U2.1), quality control (U3.1) and maintenance (U4.2) our interviewees explicitly mentioned process guiding as a potential application scenario. Moreover, even in logistics the support of picking processes (U5.1) is in fact process guiding of logistic workers. Finally, the incorporation of employees in practical workflows (U1.1) can be considered as process guiding as well. However, in the last case the smart glasses need to provide much more detailed information to the workers in order to successfully provide guidance because those workers are not yet familiar with the workflow during their on-the-job training.
Further similarities can be identified between remote support (U6), the supervision of learners (U1.2) and demonstrating practical knowledge in formal settings (U1.3). In all three cases the aim of using smart glasses is to record a special situation hands-free (e. g. an error, the execution of a workflow or a demonstration of practical knowledge) and to present the resulting live videos (e. g. to a remote expert, a teacher or a class). Even the reporting of defect items (U5.2) and the documentation using video recordings (U3.2) are similar to the other application scenarios mentioned above, as in these scenarios the capture of pictures and videos is required.
Finally, the provision of different kind of additional information as presented in four use cases (U2.2a, U2.2b, U2.3 and U4.1) can be grouped together. In all cases smart glasses need to present information which has the aim of supporting workers: In U2.2a and U2.2b further background information or anomalies should be displayed; In U2.3 the worker should be motivated by providing feedback about the current work performance and in U4.1 additional sensor data of machineries should be provided.
These application scenarios discussed above should be considered in further research and practice projects. Especially, the three identified groups of technical similar application scenarios could be used as a foundation for further in-depth analysis: From a technical perspective it is reasonable to examine the three groups separately by determining requirements, developing artefacts and evaluating them in practice (e. g. by conducting laboratory experiments). In the first case – guidance of workers – a prototype should be developed which is able to display step-by-step instructions. In order to enable a use in different application scenarios (e. g. U2.1 and U3.1) the information provided to the worker should be customizable to meet the different business requirements. In this way, one prototype can cover multiple application scenarios.
In the second case – recording – two different functionalities need to be analyzed: live streaming of video and audio as well as the creation of video recordings which need to be stored for further usage (e. g. for documentation). In addition to that, the required technical infrastructure should be examined as well, because live streaming of video and audio has high demands on the IT infrastructure (e. g. wireless LAN coverage in the industrial production facilities and a fast and reliable internet connection). For this reason, the available technical conditions at the operation side need to be considered when prototypes are developed.
Finally, the last group of application scenarios differs from the others as the provision of information varies a lot depending on the business requirements, e. g. if live sensor data should be provided to workers, interfaces to machines are required. In other cases only static information (like CAD drawings) is needed. Thus, in contrast to the other groups, a prototype which implements a scenario of the last group – provision – should focus on a concrete scenario. In addition to that, the technical suitability of smart glasses for the selected scenario should be analyzed as well. For instance, it should be examined if the available screen space is sufficient to display high-resolution CAD drawings to factory workers.
6 Conclusion
In this research paper, we pursued the goal of identifying application scenarios in the industrial sector. Based on 21 interviews with domain experts, we derived 15 application scenarios in industries in four business process (manufacturing, quality control, maintenance and logistics) and two cross-sectional tasks (employee training and remote support). Furthermore, we were able to cluster the identified application scenarios in three different technical groups (guidance, recording, provision). Each group consists of several application scenarios which have commonalities from a technical perspective. As a next step, requirements should be analyzed in detail in order to implement prototypes which can be used for evaluating the identified application scenarios in practice.
About the authors
Sebastian Hobert studied Applied Computer Science at the Georg-August-Universität Göttingen. Since 2014, he works as a research associate and doctoral student at the Chair of Application Systems and E-Business. His research focuses on the use of wearable computers in industries.
Since 1991, Prof. Dr. Matthias Schumann is a tenured professor at the Georg-August-Universität Göttingen and holds the Chair of Application Systems and E-Business. He leads the computing center of the faculties of economic and social sciences. His research interests include the use of ubiquitous, mobile and wearable systems in enterprises, the use of IT for resource efficiency, knowledge management and virtual learning.
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