Passive Exoskeletons to Enhance Workforce Sustainability: Literature Review and Future Research Agenda
Abstract
:1. Introduction
2. Methodology
3. Descriptive Analysis
4. Content Analysis
4.1. Task-Based Categorization
4.1.1. No-Overhead Assembly
4.1.2. Overhead Assembly Tasks
4.1.3. Manufacturing Tasks
4.1.4. Material Handling Tasks
4.1.5. Order Picking Tasks
4.1.6. Motion-Related Tasks
4.2. Guidelines and Methodological Criteria
4.3. Simulation Studies
4.4. Framework and Survey
5. Discussion and Future Research Agenda
5.1. RQ1: Which Manual Tasks Can Be Supported by Passive Exoskeletons and Which Methods Have Been Applied to Assess Their Performance?
5.2. RQ2: How the Workers’ Height and Waist Size Influence the Exoskeleton Selection Process in Industrial Contexts?
5.3. RQ3: How Do Exoskeletons Influence Production Efficiency Regarding Time and Working Quality?
5.4. Future Research Agenda
- More focus on in-field studies: The assessment studies classified in this review focused more on simulated tasks than real ones with 35 studies versus 19, respectively. More research is needed to clearly understand the impact of passive exoskeletons in the real industrial scenario. From the literature emerges a different impact of passive exoskeletons between real and laboratory-simulated tasks. In fact, Bosch et al. [35] found a 38% decrease in low back muscle activity in simulated tasks while Amandels et al. [36] recorded a 12% decrease for real tasks. This remarks that a real setting can create working conditions able to generate the natural variability of movements that cannot be captured in highly controlled laboratory settings [69].
- Production efficiency impact of exoskeletons: Only 13 studies assessed the impact of passive exoskeleton deployment on production efficiency. As emerged in Section 5.3 and Table 6, the results are contrasting (i.e., [36,37]) and not sufficient to answer this question. A challenging future research question will be the study of the effects of passive exoskeletons on production efficiency in terms of both time performances and quality variations. These parameters will be concurrent in productivity, economic evaluations, and decision making.
- Injury reduction rate estimation: Occupational injuries and WRMSDs generate absenteeism at work and all related costs for workforce management and re-scheduling and loss of productivity if shifts remain unreachable due to the lack of personnel. Managers could use these two parameters to better assess the exoskeleton deployment in factories and logistic facilities in the near future even if this approach is time-consuming and requires longer testing times and several efforts by companies. However, the literature analysis highlights the potential of passive exoskeletons to limit local muscular activations, but it is not sufficient to unreservedly promote passive exoskeletons as a WRMSD prevention technology and more research is needed in this direction [30].
- Decision support system for accelerating decision-making: From a managerial point of view, there is an urgent need to develop a decision support system to guide practitioners in selecting the appropriate exoskeleton according to the tasks the workers are asked to perform and on a robust cost/benefits analysis. Several efforts were made to provide guidelines and methodological criteria as discussed in Section 4.2, but complete industrial and cost-oriented approaches are not yet available in the literature also due to a lack of different data mentioned also in the other open point of this future research agenda.
- Predictive biomechanical models: Muscle activation variations are one of the direct effects of exoskeleton support on the human musculoskeletal system. Further research should carefully address this aspect and provide new predictive biomechanical models to enable musculoskeletal simulation for forecasting muscular effort given external load and movement as inputs instead of limiting to the EMG measurement as previously conducted by Tröster et al. [124].
- Long-term physical effects of exoskeletons: Lack of long-term testing and research is also reported by the other reviews [15,16]. Since long-term effects on the human body after prolonged use of exoskeletons are still unknown, new data on this aspect will be essential for driving future developments and implementations in industrial settings. Here, the cooperation between industry and academia will be crucial and strategic. The available testing campaigns present in the published literature consider a maximum length of exoskeleton usage of 7.7 h per day over three months of industry testing [71].
- Effect of exoskeletons on workers’ diversity, comfort and technology acceptance: There is also a need for future testing activities on balanced test samples in order to understand if there are gender-based differences and guide future design developments of exoskeletons for gender equality. In the same way, also studies over test samples that cover a broader range of experience levels and workers’ age will enable the generalization of the results to a more significant part of the working population [24]. Moreover, the integration of several key concepts from the human factors engineering discipline will be strategic to assess exoskeleton use and benefits in the context of Industry 4.0. The available literature is still not effective to demonstrate if the workforce can easily accept exoskeletons. To this purpose, the comfort level measurement needs to be better and carefully assessed by future researchThe so-called “side effects of the technology” need to be investigated also for exoskeletons since there might be side effects associated with the comfort of straps and mass of the device when worn for an entire working shift of 8 h.
- Evaluation of the return on investment in exoskeletons: On the monetary side, none of the retrieved works directly studied the return on investment (ROI). Todorovic et al. [90] showed methods for the economic evaluation of technologies in the industry that could be suitable for assessments on the introduction of exoskeletons in industrial contexts. Some relevant parameters that may affect the monetary aspect have been found by analyzing existing works classified here. Time efficiency is a key and direct parameter for evaluating the impact of exoskeletons on production efficiency. By influencing task completion times or operator endurance in demanding static positions as discussed in Section 5.3, exoskeletons could produce a tangible and measurable effect on the overall throughput of a line. Moreover, the quality (the error rate in production) could be affected by the utilization of exoskeletons and the impact on overall product quality as shown by Kim et al. [72]. The loss of quality of the production process could result in increased costs if the error rate increases and more products do not pass quality control tests, making a rework activity necessary or a complete waste of the products. Finally, the injury rate reduction will reduce absenteeism and all the related costs sustained by both the company and the collectivity, and, on the other hand, the loss of production and revenue.
6. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
Appendix A
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Group 1 Appellative Keywords | Group 2 Field Keywords |
---|---|
‘exoskeleton *’ ‘exosuit *’ ‘softsuit *’ | ‘logistic *’ ‘manufacturing’ ‘industr *’ ‘assembly’ ‘production’ ‘warehous *’ ‘pick *’ |
Body Region Supported by the Exoskeleton | 1. No-Overhead Assembly | 2. Overhead Assembly | 3. Manufacturing | 4. Material Handling | 5. Order Picking | 6. Motion-Related Tasks |
---|---|---|---|---|---|---|
Back | 4 | 0 | 1 | 11 | 7 | 2 |
Upper limb | 2 | 7 | 11 | 4 | 2 | 3 |
Tool Support | 0 | 0 | 4 | 0 | 0 | 0 |
Lower limb | 5 | 0 | 1 | 0 | 1 | 1 |
Type of Task | ||||||
---|---|---|---|---|---|---|
Exoskeleton Name | 1. No-Overhead Assembly | 2. Overhead Assembly | 3. Manufacturing | 4. Material Handling | 5. Order Picking | 6. Motion-Related Tasks |
Laevo | [35,36,37] | [38,39,40,41,42,43] | [44,45,46,47] | |||
Paexo back | [48] | |||||
BackX | [37,49] | [50] | ||||
Flx ergoskeleton | [51,52] | |||||
V22 | [51] | |||||
Paexo soft back | [47] | |||||
Rakunie | [47] | |||||
Atlas | [47] | |||||
Flexible prototype beams | [53,54] | |||||
IPAE | [55] | |||||
Hero Wear Apex | [56] | |||||
Levitate | [57,58,59,60,61] | [33,62] | ||||
ShoulderX | [63,64,65,66,67] | [68] | ||||
Mate | [69] | [58] | [67] | |||
Eksovest | [70] | [71] | [72,73,74,75] | |||
Skelex | [76] | [63,74,75,77] | [68] | |||
H-VEX | [78] | |||||
IUVO | [79] | |||||
Paexo shoulder | [67,74,75] | [80] | ||||
Crimson Dynamics | [76] | |||||
Exhauss Stronger | [81] | |||||
Fawcett + ZeroG | [65,73] | |||||
Fortis + arm | [65,73] | |||||
Chairless chair | [82,83,84] | [85] | ||||
LegX | [86] | |||||
CEX | [87] | |||||
Daedalus | [47] | |||||
Leg prototype | [88] |
Assessment Methodology | ||||||||
---|---|---|---|---|---|---|---|---|
Type of task | EMG | Subjective Evaluation | Heart Rate Evaluation | Oxygen Consumption | Postural Analysis | Range-of-Motion Analysis | Time Performance Measurement | |
1. No-overhead assembly | 8 | 11 | 0 | 0 | 3 | 1 | 4 | |
2. Overhead assembly | 2 | 7 | 0 | 0 | 1 | 1 | 1 | |
3. Manufacturing | 15 | 10 | 1 | 0 | 0 | 0 | 3 | |
4. Material Handling | 8 | 9 | 2 | 2 | 6 | 4 | 5 | |
5. Order Picking | 3 | 5 | 1 | 0 | 1 | 0 | 0 | |
6. Motion-related | 1 | 1 | 0 | 0 | 3 | 1 | 0 |
Exoskeleton | Min. Height Size | Max. Heigh Size | Min. Waist Size | Max. Waist Size |
---|---|---|---|---|
Laevo (ref. to FLEX version) | 150 | 200 | 34 (hip width) | 43 (hip width) |
Paexo back | S | XL | Adjustable | Adjustable |
BackX | 5–95% of human dimensions | |||
Flx ergoskeleton | 167 | 213 | 68 | 130 |
V22 | 167 | 213 | 68 | 130 |
Paexo soft back | NA | NA | 80 | 140 |
Rakunie | 148 | 195 | 71 | 128 |
Atlas | 170 | 185 | Adjustable | Adjustable |
Flexible prototype beams | Adjustable | Adjustable | Adjustable | Adjustable |
IPAE | Adjustable | Adjustable | Adjustable | Adjustable |
Hero Wear Apex | 50+ module combination | |||
Levitate | 157 | 183 | Adjustable | Adjustable |
ShoulderX | 5–95% of human dimensions | |||
Mate | 160 | 190 | Adjustable | Adjustable |
Eksovest | 37 (torso length) | 59 (torso length) | 66 | 118 |
Skelex (ref. to 1.4.2 version) | 44 (torso length) | 54 (torso length) | 84 | 124 |
H-VEX | Adjustable | Adjustable | Adjustable | Adjustable |
IUVO | 160 | 190 | Adjustable | Adjustable |
Paexo shoulder | 160 | 190 | Adjustable | Adjustable |
Crimson Dynamics | 165 | 195 | Adjustable | Adjustable |
Exhauss stronger | Adjustable | Adjustable | S | L |
RoboMate passive | NF | NF | NF | NF |
Fawcett + ZeroG | Adjustable | Adjustable | Adjustable | Adjustable |
Fortis + arm | 162 | 193 | Adjustable | Adjustable |
Chairless chair | 150 | 200 | Adjustable | Adjustable |
LegX | Adjustable | Adjustable | Adjustable | Adjustable |
CEX | 160 | 195 | Adjustable | Adjustable |
Daedalus | NF | NF | NF | NF |
Leg prototype | 33 (thigh and leg) | 43 (thigh and leg) | Adjustable | Adjustable |
Publication | Exoskeleton | Task Type | Findings |
---|---|---|---|
[35] | Laevo | Static | Endurance time increased >3×(from 3.2 to 9.7 min) |
[41] | Laevo | Static | Endurance time increased ≈2× |
[88] | Leg prototype | Static | Endurance time increased from 2.76 to 13.58 min |
[62] | Levitate | Static | Endurance time increased 31.6% |
[57] | Levitate | Static | Endurance time increased 52.5% |
[79] | IUVO | Static | Endurance time increased 56% |
[72] | Eksovest | Static | Completion time decreased 18.9% |
[50] | BackX | Static | Completion time decreased up to 50% |
[63] | ShoulderX, skelex | Static | Completion time not always decreasing |
[36] | Laevo | Dynamic | Completion time decreased 15% |
[49] | BackX | Dynamic | Completion time increased 7.6% for females |
[52] | Flx Ergoskeleton | Dynamic | Completion time increased 20% |
[39] | Laevo | Dynamic | Completion time increased 8% |
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Ashta, G.; Finco, S.; Battini, D.; Persona, A. Passive Exoskeletons to Enhance Workforce Sustainability: Literature Review and Future Research Agenda. Sustainability 2023, 15, 7339. https://doi.org/10.3390/su15097339
Ashta G, Finco S, Battini D, Persona A. Passive Exoskeletons to Enhance Workforce Sustainability: Literature Review and Future Research Agenda. Sustainability. 2023; 15(9):7339. https://doi.org/10.3390/su15097339
Chicago/Turabian StyleAshta, Gjulio, Serena Finco, Daria Battini, and Alessandro Persona. 2023. "Passive Exoskeletons to Enhance Workforce Sustainability: Literature Review and Future Research Agenda" Sustainability 15, no. 9: 7339. https://doi.org/10.3390/su15097339
APA StyleAshta, G., Finco, S., Battini, D., & Persona, A. (2023). Passive Exoskeletons to Enhance Workforce Sustainability: Literature Review and Future Research Agenda. Sustainability, 15(9), 7339. https://doi.org/10.3390/su15097339