Effect of low-cost automation on labor productivity and labor fatigue for corrugated boxes flaps twisting

Abstract

BACKGROUND:

Flaps of the corrugated box folded inversely while manual packing of goods initiative this will cause tearing of the box at creased positions.

OBJECTIVE:

To avoid tearing, it is required to twist each box along creased positions as soon as it is manufactured and in wet condition due to liquid gum application.

METHODS:

To apply and evaluate the effect of Low-Cost Automation on labor productivity and labor fatigue for corrugated boxes flaps twisting. Low-Cost Automation solution is applied to overcome low labors’ productivity and excessive labors’ fatigue problems in the manual box twisting work. Productivity need analysis is performed to identify the key productivity measures. Three automated mechanisms are developed for box stopping, clamping, and twisting activities.

RESULTS:

Reduction in labors muscular efforts requirement is confirmed through surface electromyography technique. It is observed that the average actual time required for twisting one box reduced from 34 seconds to 17 seconds, and labor productivity almost doubled. The muscular efforts required for twisting of flaps of the boxes are reduced significantly.

CONCLUSION:

The developed low-cost automation solution is unique and found worthy for small scale corrugated box manufacturers.

Keywords

Electromyography labor productivity labor fatigue low cost automation (LCA)mechatronics productivity need analysis (PNA)

1 Introduction

The term “raisin” in the English language is often used for dried grapes. India accounts for 1.20 percent of the total share of raisins export in the world. Maharashtra and Karnataka states contribute about 96.13 percent of India’s grapes production from which raisins are produced [1]. Raisins are usually packaged in corrugated boxes with a plastic bag inside the box. While manual packing of raisins, initially, the plastic bag is kept in an empty box, the box’s flaps are folded inversely. Furthermore, the plastic bag’s open end is hanged in folded flaps; raisins are poured in a plastic bag; after having some specific weight of raisins, the bag’s hanged open end is removed from the flaps, and a knot is applied. Finally, the flaps are closed and sealed by using gluing tape. The existing process of box folding and unfolding is shown in Fig. 1. The corrugated box tears along creased positions when the flaps are folded inversely for hanging plastic bag. The corrugated boxes are produced using paperboards, consisting of different layers of papers glued together using liquid gum. The paperboards used for box manufacturing become wet due to liquid gum application during gluing operation to stick different papers together. It is required to twist each box twice or thrice at creased positions when it is in wet conditions so that it should not tear away at creased positions when it becomes dried. Twisting at creased positions is a unique requirement of the boxes used for manual packing of raisins followed by smallest scale and medium scale raisins packing, marketing, and distributing agencies. The other way to avoid tearing of boxes at creased positions is to use the virgin or non-recycled paperboards, which have a higher burst factor while manufacturing the boxes. Due to economic considerations, corrugated box manufacturers prefer to use recycled paperboards and twist each box manually twice or thrice at creased positions in a wet condition.

The used corrugated boxes are collected and processed to prepare the recycled paperboards. Over 76 % of corrugated boxes are recollected to prepare the paperboard from which again the more boxes are produced [2]. Again, using recycled paper for manufacturing boxes is green production, essential for sustainable development [3]. The Low-Cost Automation (LCA) is an approach that enables the industries to improvise the manufacturing methods and manufacturing efficiency instead of purchasing costly machinery. In developing countries like India some design interventions are required to reduce the manual efforts [29 –34]. It involves using standard parts, devices, and accessories that are readily available in the market to mechanize and automate existing machines, processes, and systems [4]. The manual work can be reduced by implementing the automation in production, but classic automation, most preferred in the western world, is often set up of full-automation, which is expensive and complicated. India’s small manufacturing firms’ growth barriers are lack of financing, regulatory issues, and infrastructure [5]. The practical, safe, economical, and rewarding strategy in these circumstances is the application of LCA. The LCA can be implemented intelligently to automate the individual tasks that require precise and strategic decisions [6]. The LCA is a prominent tool for improving labor productivity by reducing active human participation in boring, monotonous, and fatiguing industrial tasks. It can enhance worker productivity and provide safety, physical and mental well-being, and job satisfaction for workers [7]. Singh et al. recommended implementing LCA in developing countries’ industrial production to perform better in a highly dynamic world [8]. Malaikaew and Jaojaruek used the 4-axis robot arm for corrugated boxes palletizing work for reducing labor intervention and cycle time and improving productivity [9]. Khire et al. had developed a carton-folding device that involves the specially designed fixture and former to fold the corrugated paper cartons, which are used for the packaging of export quality grapes [10]. Liang et al. reported the use of a SCARA robot for folding cartons. The folding sequence was developed as a robot motion-planning problem where a carton is treated as an articulated robot with revolute joints and a branching sequence of links [11]. Yao et al. investigated reconfigurable technology using robotics for folding cartons in the confectionery industry [12]. Dai et al. outlined a case study of a reconfigurable demonstration system in the confectionery industry [13]. Balkcom et al. developed four degrees of freedom adept SCARA robot arm to make simple folds [14]. Marschke used rotating wheels or spiral bars at different orientations to fold carton panels at their creases as the carton blank moves past [15]. Productivity need analysis (PNA) is the methodology that provides an overview of the current manufacturing conditions and identifies the productivity affecting measures. The PNA matrix provides information regarding relations and the strength of relations among the manufacturing problems and the various tools/techniques available to solve the identified manufacturing problems.

Fig. 1

Existing process of box folding and unfolding.

Electromyography is the technique for detecting and analyzing electromyogram (EMG), i.e. the signals used to measure the muscle fatigue parameters. Cavalcanti et al. concluded that by placing the electrodes on the skin’s surface or inserting in the muscle tissue, it is possible to study how the controlling commands issued by rowers or figure skaters translate into muscle activation [16]. Merletti et al. and Vigotsky et al. detected factors other than muscular efforts that influence the myoelectric signal, including muscle length, contraction mode, contraction speed, etc. Muscle fatigue can be measured through different techniques but require expensive instruments [17, 18]. Sergio et al. checked muscle fatigue using low-cost surface EMG sensors, a computer, and an Arduino board. The experimental work proved the reliability of a developed low-cost system for the measurement of muscle fatigue. Validation and comparison of the low-cost system are made against commercially available accurate devices, and the agreement of the results between both systems is excellent. The performed work proved the hypothesis that the root mean square (RMS) and mean absolute value (MAV) increase while mean frequency (MNF) decreases when fatigue appears [19].

The Corrugated Box Manufacture Association of Western Maharashtra of India is an association of small scale corrugated box manufacturers, demanded the concrete solution to overcome the problems of labors productivity and labors fatigue related to manual box twisting work. Even though many problems have been addressed using LCA in the past, none of the work attempted to use LCA for corrugated box twisting along creased positions. In the present paper, the total work is organized into steps such as quantifying labor productivity through industrial engineering techniques and labor fatigue through surface electromyography technique, performing PNA to identify the productivity affecting measures. Development of the flaps twisting mechanism; interfacing twisting mechanism with box stopping and clamping de-clapping mechanism; and trials and performance analysis to confirm improved labor productivity and labor fatigue reduction.

2 Experimental protocol

Part 1: Manual box twisting method

The time study of manual box twisting work is carried out, consisting of five sequential activities. Twelve work trials are carried out, and activity-wise time required in seconds is tabulated in the sheet, as shown in Table 1. The Average actual time required to twist one box is approximately 34 seconds. Out of five activities, activity number 2 and 4 are consuming more time.

Table 1
Average actual time required to twist one box

Activity Description Time (seconds) Activity

no. of activity Trial 01 Trial 02 Trial 03 Trial 04 Trial 05 Trial 06 Trial 07 Trial 08 Trial 09 Trial 10 Trial 11 Trial 12 wise average time (seconds)

1 Pick box from a stack and put it on work the table 6 7 7 6 6 7 7 7 6 7 7 7 6.67

2 Twist flaps on one side (by two workers) 8 8 9 8 8 8 9 9 8 8 9 8 8.33

3 Turn over the box 5 4 5 6 5 5 4 5 5 5 5 5 4.92

4 Twist flaps on the other side (by two workers) 8 8 9 8 8 8 8 8 8 8 9 7 8.08

5 Pick box from the work table and put in a stack 6 6 6 5 7 6 7 6 6 6 6 6 6.08

Average actual 33 33 36 33 34 34 35 35 33 34 36 33 34.08

total time required

to twist one box

Activity	Description	Time (seconds)	Activity
1	Pick box from a stack and put it on work the table	6	7	7	6	6	7	7	7	6	7	7	7	6.67
2	Twist flaps on one side (by two workers)	8	8	9	8	8	8	9	9	8	8	9	8	8.33
3	Turn over the box	5	4	5	6	5	5	4	5	5	5	5	5	4.92
4	Twist flaps on the other side (by two workers)	8	8	9	8	8	8	8	8	8	8	9	7	8.08
5	Pick box from the work table and put in a stack	6	6	6	5	7	6	7	6	6	6	6	6	6.08
Average actual	33	33	36	33	34	34	35	35	33	34	36	33	34.08
total time required
to twist one box

As the boxes are twisted manually, the count of boxes twisted in first and second shifts varies and depends on the workers’ performance. The average actual total numbers of boxes twisted per shift are calculated by considering fifteen days; two shifts data, as shown in Table 2.

Table 2

Average actual total numbers of boxes twisted in one shift

Day	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	x
Shift I	430	441	431	422	417	421	412	422	418	421	439	425	427	429	427	425.5
Shift II	427	409	398	412	407	394	395	389	397	402	407	399	392	401	407	402.4
Average	428.5	425	414.5	417	412	407.5	403.5	405.5	407.5	411.5	423	412	409.5	415	417	413.9

*x- Average actual total numbers of boxes twisted in one shift.

The corrugated box manufacturing industries under study are small scale industries, and most of them work in two shifts. The total number of working hours available per shift is seven by considering all workers’ breaks. By referring average actual total numbers of boxes twisted in one shift, the conventional manual box twisting method’s efficiency is calculated as shown in Table 3 is 55.81 %, which is considerably less and highlights the lack of productivity.

Table 3

Efficiency of conventional manual box twisting method

Number of seconds available in one shift (considering seven working hours per shift)	25200
Average actual total time required to twist one box in seconds	34.08
Number of boxes expected to be twisted in one shift (considering zero downtime) [25000/34]	739.43≈740
Average actual total numbers of boxes twisted in one shift (considering fifteen days data)	413.9≈413
Total less number of boxes twisted per shift due to non-performance of workers (considering all valid and invalid downtime reasons) [740-413]	327
The efficiency of the conventional manual box twisting method	55.81%

Experimental work has been performed for collecting the data of muscle efforts measurement for manual box twisting. A healthy male subject aged 35 years was involved in this study, having previous box twisting experience in the corrugation industry. The subject was right-handed dominance and not previously suffered by considerable musculoskeletal injuries. The production target was the participative target in which the subject is allowed to work at his own pace, and no standard time is allotted to accomplish the work. In this experimental work, the surface electromyography technique was applied to measure forearm muscle activity. The surface electrodes and prepared associated electronic circuit measures filter, rectify, and amplify a muscle’s electrical activity. This circuit produces an analog output signal that the microcontroller can easily read and converts into digital signals. The mounting of surface electrodes is shown in Fig. 2.

Fig. 2

Mounting of surface electrodes.

A sensor is designed to be used directly with a microcontroller; it gives amplified, rectified, and smoothed EMG signals which work well with a microcontroller’s analog-to-digital converter (ADC). The prepared electronic circuit for the measurement of muscle activity as shown in Fig. 3.

Fig. 3

Setup to measure muscle activity. 1 computer, 2 arduino board, 3 surface electromyography sensor, 4 volunteer.

In this study, two indicators (RMS and MAV) related to the amplitude andthird indicator (MNF) related to the mean frequency were calculated.Arduino Uno R3 ATmega 328P is used as a microcontroller and programmed to calculate and display the above three parameters on the computer screen. The algorithm to calculate these parameters is developed by referring to the below formulae [20]. $MAV = 1 / N \sum_{i = 1}^{N} | x_{i} |$ (1) $RMS = \sqrt{1 / N \sum_{i = 1}^{N} x^{2}}$ (2) N is the number of samples and x_i the value of the signal in the i sample. $MNF = \frac{\sum_{j = 1}^{M} f_{j} P_{j}}{\sum_{j = 1}^{M} P_{j}}$ (3)

f is the frequency value of the EMG power spectrum in frequency interval j, Pj is the EMG powerspectrum in frequency interval j, and M is the length of the frequency interval. The observed values of RMS, MAV, and MNF are discussed in detail in the next part of the paper. Referring to the results time study, productivity study, and electromyography, it was proposed to implement an LCA solution to improve productivity and reduce the muscular efforts requirement.

Part 2: Methodology for implementing LCA

The proposed methodology for implementing LCAposses three steps. The first step is performing PNA, which provides a numerical score that identifies the productivity affecting issues. The second step isthe development of an appropriate LCA solution intwo steps: mechanization and automation.The last step is the implementing developed LCA solution and its performance evaluation through conducting working trials.

2.1 Productivity need analysis

The PNA matrix is developed by taking into account the various activities needed to twist the flaps of corrugated boxes, the available resources the focused industries, feasible solution techniques, and the various problems arrived during manual twisting. The scoring is done in reference to the relationship among the elements of the matrix. The established PNA matrix indicating the relationship and the scoring is shown in Fig. 4.

Fig. 4

PNA matrix.

Major influence (strong relationship) –nine points - •

Significant influence (medium relationship) –three points- ∘

Minor influence (weak relationship) –one point- Δ

Activities (A): Five different sequential activities needed to twist the corrugated box’s flaps are defined. In this case, out of five activities, activity numbers 2 and 4; twist flaps on one side and twist flaps on the other side are the key activities.

Resources (B): The available resources in the research sponsoring industries to achieve targeted production.

Techniques (C): The potential solution techniques, through which identified problems could be addressed.

Process problems (D): These are the significant problems in the manual box twisting process identified and quantified using various industrial engineering techniques such as time study and electromyography.

The first relationship is between the activities (A) and the resources (B). The second relationship is between the resources (B) and the process problems (D). The third relationship is that between the process problems (D) and the techniques (C). The fourth relationship is between the techniques (C) and the activities (A).

The established PNA matrix is post-processed in the clockwise direction. The main activities are referred as a starting point, and the relationship between the other elements is gradually scored. After scoring the relationships among all the elements, the overall score is obtained by performing respective additions. As an example the overall score calculation between the relationship of main activities and cycle time is; 3 + 9 + 9 + 9 + 3 = 33. The significant interactions among the various elements of the established PNA matrix are indicated by using alphabets, as shown in Table 4. The post-processing of the established PNA matrix suggested that the first intervention should take place in the flaps twisting activities and discussed in detail in the next part of the paper.

Table 4

Significant interactions among the various elements of established PNA matrix

E	Relation between activities and resources
F	Activities with the highest interaction with the resources
S	Activities having the highest interaction between both techniques and resources
H	Activity characteristic interaction with the resources and problems
I	Problem with the highest interaction with tools and resources
J	Resource with the highest interaction with the process problems
K	Resource with the most relevance to the activities and process problems
L	Improvement tool that has the highest reaction to processes and process problems
M	Tool with the highest relevance to process problems
N	Low productivity problem most aligned with the tools
P	Activities that most interact with the tools
R	Tools with the highest interaction with the current processes

2.2 Mechanization and automation

The developed LCA system consists of three mechanisms viz box twisting mechanism, box stopping mechanism, and box clamping de-clamping mechanism. The basic LCA principle isto utilize maximum standards parts available in the market while designing the system so that capital investment inautomation will be less and the payback period will be shorter [21, 22]. While designing all these three mechanisms, this principle was followed rigorously. The Understand, Simplify, and Automate (USA)principle is a common-sense approach applied in automation projects [23], and the same was implemented while designing the box twisting mechanism. A new box twisting mechanism was developed to twist both sides’ flaps simultaneously to reduce twisting time and for the complete elimination of muscular efforts required for twisting activities. Three dimensional CAD modelwas prepared,and kinematic simulation of the proposed mechanism was performed using software CATIA V6.Improvements are incorporated one by one until the mechanism is optimized within all the constraints for its proper functioning. The wireframe CAD model of the developed box twisting mechanism is shown in Fig. 5. During clockwise and anticlockwise motion, the mechanism causes twisting both sides flaps simultaneously in a single work cycle.The mechanical components like timing belts, timing pulleys, bush, and bearing blocks required for building the mechanism are used from the automotive scraps, which are the standard parts readily available in the market at an affordable cost.

Fig. 5

Wireframe CAD model of the box twisting mechanism. 1. timing pulley, 2. bush block, 3. moving arm, 4. guide bars, 5. bracket, 6. arm shaft, 7. base plate, 8. table, 9. hub, 10. pulley spacer, 11. pedestal bearing, 12. driving shaft.

The driving shaft receives power from the geared electric motor and transmits it to four moving arms through timing belts and pulleys for twisting box flaps in clockwise and anticlockwise directions. The box to be twisted passed through the guide bars of the twisting mechanismand moved further. It is required to stop the box’s further movement and inform the box’s availability to the control system. Two box stopper mechanisms are developed for the same and mounted on a twisting mechanism. The inserted box will press the arms of limit switches mounted on stopper mechanisms, and the box’s further motion will be restricted. The box clamping de-clamping mechanism was developed to secure the box firmly during the twisting action. Two limit switches are mounted on the mechanism to detect and control the bracket’s position of the clamping de-clamping mechanism with which the box will be secured.

Once implementing mechanization to reduce human muscular efforts, there is a need to take the support of electrical, pneumatic, hydraulic, and similar other actuators during automation. Muscles are keys to the mobility and manipulation capabilities of biological creatures, and when developing robots and automation systems, it is important to have actuators that allow the emulation of the behavior and performance of real muscles [24]. Utilizing electrical power as a source of energy can reduce approximately 400 times at a cost than to get the same amount of energy from human beings [25].The torque calculations have been carried out to run the proposed twisting mechanism. The torque required to run the twisting mechanism in free conditions (M_free) was found equal to 4.3 N-mm. The torque required for twisting flaps of the box was found by preparing the experimental set up (M_twist) equal to 15.7 N-mm. So total torque required to run the twisting mechanism (M_total) was 20 N-mm. So, the standard geared motor having torque 22 N-m was selected. Though the motor runs at twelve volts, the ampere required changing as per torque requirements up to 10 Amp, and the sophisticated SMPS provided for the same.

In automation systems, apart from reducing physical human participation, it was expected that the system must be capable of doing mental work as in the case of computer numerical control machines [26, 27].To cater to the need to do mental work that coordinates and synchronizes three mechanisms, the Arduino Mega 2560 board was used as a controller. As the proposed system is an application of LCA; the low cost of Arduino hardware and it is free software encouraged using it as a control device rather than PLC. Arduino has proved its effectiveness as a controller for many real applications [28]. It has enough capabilities to run the developed automation system. In the proposed automation system, three different mechanisms were powered by electrical motors and controlled and coordinated by an electronic control system; thus, this automation system is an excellent example of Mechatronics based machine development and concurrent design synergy. The box stopping mechanism, clamping de-clamping mechanism, and twisting mechanisms are integrated using various electronic devices, as shown in Fig. 6. The potentiometer is used as a sensor to detect and control the position of the driving shaft. The buzzer is used to get a short beep sound after twisting each box and a long beep sound once twenty-five number of boxes twisted. LCD is provided to get an online count of the number of boxes twisted. The reset switch is provided to reset the LCD to zero counts. On-off lamps are provided for indicating the start and stop of the work cycle. The flowchart referred while preparing the control logic or algorithm of the automation system is given in Fig. 7.

Fig. 6

Block diagram of the system.

Fig. 7

Algorithm flowchart of the automation system.

3 Results and discussion

The relationships and the final scores obtained between the activities and the various problems in the manual twisting work are given in Fig. 8 by referring the PNA matrix.

In Fig. 4, scores S indicates the relationship among activities and resources. In Fig. 8, scores T indicates the relationship among activities and process problems. These two scores are added together to identify the productivity affecting activities that need to be addressed. The results of the addition of these scores are presented in Table 5. The results in Table 5 propose that the highest score (118) is for the flaps twisting activities, and hence these activities are the needs to be addressed on a priority basis.

Fig. 8

Matrix indicating relationships between activities and process problems.

Table 5

Addition of scores S and T to identify the productivity affecting activities

Activities	S	T	S+T
Pick box from the work table and	22	9	31
put in a stack
Twist flaps on another side	82	36	118
Turn over the box	30	11	41
Twist flaps on one side	82	36	118
Pick box from a stack and put it	22	9	31
on the work table

The total number of manual activities required to twist the box with the conventional method is five, whereas the number ofmanual activities required to twist the box with a developed automation system is only two. One activity is to load the box;another activity is to unload the twisted box.In between these two manual activities, box flaps will be twisted by the system automatically without human intervention. The average actual time required for twisting one box reduced from 34 seconds to 17 seconds. Figure 9 illustrates the activity-wise variation in cycle time for box twisting before and after implementing the automation.

Fig. 9

Variation in cycle time for box twisting before and after implementing automation.

An experimental task was conducted to collect the data of muscle efforts measurement during automated box twisting. RMS, MAV, and MNF values of the manual box twisting trials, and automated box twisting trials are compared in Table 6. The last row of Table 6 indicates percentage variation in RMS, MAV, and MNF; by referring these values, it can be concluded that there is a reduction in muscular efforts required for automated twisting of flaps of the boxes. The operator’s role is limited to just to load and unload the boxes that demand fewer amounts of muscular efforts.

Table 6

Comparison of RMS, MAV, and MNF values of ten manual box twisting trials

Trial number	MAV		RMS		MNF
	Manual twisting	Automated twisting	Manual twisting	Automated twisting	Manual twisting	Automated twisting
1	70.43	22.85	65.27	24.13	19.32	22.49
2	61.99	25.86	51.34	27.04	19.87	27.46
3	67.39	29.14	59.51	30.24	20.00	21.67
4	71.89	21.28	64.51	22.81	20.20	21.23
5	73.67	24.80	63.80	26.02	21.76	22.82
6	73.85	29.71	62.36	25.54	20.68	34.49
7	73.90	32.31	62.17	30.36	21.46	27.16
8	60.77	29.46	52.29	30.63	21.76	22.72
9	61.91	28.58	57.65	29.77	21.38	27.97
10	63.98	31.50	62.37	32.10	18.90	24.83
Average	67.98	27.55	60.13	27.86	20.53	25.28
% reduction	59.47%		53.66%		-23.13%

The cycle time of the developed automation system to twist the box is 17 seconds, which is the ideal cycle time (Tc) without considering any breakdowns. The automation system’s performance can be measured in two different ways –the proportion of uptime and the proportion of downtime. The proportion of uptime indicates the time for which a machine is available to perform production activity. While operating any automation systems, there are some random breakdowns and planned stoppages, which will result in downtime [23, 36]. The various performance measures of developed the LCA system are given in Table 7, based on 15 days’ data.

Table 7

Performance measure of developed LCA system

n	N	P	Td avg	F F=P/N	Td avgcyl (F*Td avg)	Tp T p = Tc+(F*Td)	Rp R p = 1/Tp	E E=Tc /Tp	D D=(F*Td)/Tp
1	1100	42	720	0.038	27.491	44.491	0.022	38.210	61.790
2	978	39	841	0.040	33.537	50.537	0.020	33.639	66.361
3	1202	22	705	0.018	12.903	29.903	0.033	56.850	43.150
4	900	34	910	0.038	34.378	51.378	0.019	33.088	66.912
5	774	23	1100	0.030	32.687	49.687	0.020	34.214	65.786
6	1030	27	443	0.026	11.613	28.613	0.035	59.414	40.586
7	977	26	741	0.027	19.720	36.720	0.027	46.297	53.703
8	1021	18	722	0.018	12.729	29.729	0.034	57.184	42.816
9	998	37	922	0.037	34.182	51.182	0.020	33.215	66.785
10	878	27	845	0.031	25.985	42.985	0.023	39.549	60.451
11	1011	36	679	0.036	24.178	41.178	0.024	41.284	58.716
12	933	43	890	0.046	41.018	58.018	0.017	29.301	70.699
13	610	39	1003	0.064	64.126	81.126	0.012	20.955	79.045
14	988	42	978	0.043	41.575	58.575	0.017	29.023	70.977
15	1001	33	888	0.033	29.275	46.275	0.022	36.737	63.263
Average	960.067	32.533	825.800	0.035	29.693	46.693	0.023	39.264	60.736

N - Day number

N - Number of boxes twisted during shift

P - Number of times system stopped working during the shift

Td avg - Average time for which system stopped working during each stop

F - Downtime frequency, system stops per box

Td avgcyl - Downtime averaged on a per cycle basis

Tp - Actual average production time

Rp - Actual average production rat

E - System efficiency

D - Proportion of downtime

The numbers of boxes twisted in fifteen days by the conventional manual method and with a developed LCA system are compared in Fig. 10. By referring to Fig. 10 and summarized information in Table 7, it is clear that with a developed LCA system, it is possible to twist approximately 960 numbers of boxes in a shift, which are more than double the conventional manual method. One more significant inference is that the day-wise numbers of boxes twisted by the conventional manual method are half but almost constant, but there is drastic variation in the number of boxes twisted by developed LCA system. As per formulae given in Table 6, the system efficiency [E] is dependent upon the number of times the system stopped working during shift [P], and downtime averaged on a per cycle basis [Td avgcyl]. Values of terms P and Td avgcyl are randomly distributed and significantly high, and due to this, the values of the term E are also not consistent and uniform. This poses questions on the developed system’s reliability and demands to perform the work in that direction. The final model of the developed LCA system is shown in Fig. 11.

Fig. 10

Comparison of numbers of boxes twisted manually and with a developed LCA system.

Fig. 11

Developed LCA system.

4 Conclusion

LCA solution is prepared and implemented successfully to overcome the problems of less labor productivity (413 boxes/shift) and considerable muscular efforts needed to apply. The PNA matrix’s post-processing suggested that the first intervention should take place in the flaps twisting activities because of the highest score (118).Total manual activities required for the box twisting are reduced to 2 from 5. With a developed LCA system, it is possible to twist 960 boxes per shift as the cycle time reduced to 17 seconds from 34 seconds. The EMG signals analysis shown that RMS, MAV values increased by 59.47% and 53.66% successively, and MNF values reduced by 23.13%. This confirmed the effectiveness of implementing LCA for the reduction of labors’ muscular efforts. The total cost incurred for developing the LCA system is significantly low and economically viable for the sponsoring industry. The developed LCA system can make more reliable and efficient after finding affecting parameters and taking suitable corrective technical actions.

Footnotes

Acknowledgments

The authors wish to acknowledge the authorities of the Corrugated Box Manufacture Association of Western Maharashtra, India for their financial and practical support provided to develop the LCA system and to conduct trials.

Conflict of interest

The authors declare no potential conflicts of interest with respect to the research, authorship, and publication of this article.

References

Kerutagi

, Pavithra

, Byahatti

. Production and marketing of raisins in vijayapura district –an economic analysis, International Journal of Current Microbiology and Applied Sciences. 2018;7(9):658–67.

Kit

. Packaging Technology, 3rd ed., John Wiley & Sons 2010;1:170.

. Mittal

. Adoption of green manufacturing in Indian manufacturing industry: a fuzzy analytical hierarchy process approach for inhibitors. International Journal of Industrial and Systems Engineering. 2017;27(2):255.

Samuel

, Darwin

. Design and implementation of low-cost automation system in heavy vehicle brakes assembly line. International Journal of Productivity and Quality Management. 2009;4(2):199–211.

Ojha

, Vrat

. Prioritising factors for manufacturing growth in India: an analytic network process approach. International Journal of Industrial and Systems Engineering. 2018;28(1):32–52.

Seifermann

, Böllhoff

, Metternich

, Bellaghnach

. Evaluation of work measurement concepts for a cellular manufacturingreference line to enable low-cost automation for lean machining,Procedia CIRP. 2014;1(17):588–593.

Shikdar

, Hadhrami

. Smart workstation design: an ergonomics and methods engineering approach, International Journal of Industrial and Systems Engineering. 2007;2(4):363–374.

Singh

, Khamba

. An Interpretive Structural Modelling (ISM) approach for Advanced Manufacturing Technologies (AMTs) utilisation barriers. International Journal of Mechatronics and Manufacturing Systems. 2011;4(1):35.

Malaikaew

, Jaojaruek

. Palletizing robot application in the corrugated box industry. Applied Science and Engineering Progress. 2019.

10.

Khire

, Madnaik

. Folding cartons using low-cost automation –a case study. Assembly Automation. 2001;21(3):210–212.

11.

Lu. Liang . Akella

. Folding cartons with fixtures: a motion planning approach. IEEE Transactions on Robotics and Automation. 2000;16(4):346–356.

12.

Yao

, Dai

, Medland

, Mullineux

. A reconfigurable robotic folding system for confectionery industry. Industrial Robot: An International Journal. 2010;37(6):542–551.

13.

Dai

. Robotics and automation for packaging in the confectionery industry. Robotics and Automation in the Food Industry. 2013;1:401–419.

14.

Balkcom

, Mason

. Robotic origami folding. The International Journal of Robotics Research. 2008;27(5):613–27.

15.

Marschke

. Folding of paperboard sheets and the like, US Patent 4834696, 1989.

16.

Cavalcanti

, Vieira

. Surface electromyography: Why, when and how to use it. Medicina del Deporte. 2011;4(1):17–28.

17.

Merletti

, Farina

. Surface Electromyography: Physiology, Engineering, and Applications, in John Wiley & Sons. 2016;1, 1–16.

18.

Vigotsky

, Halperin

, Lehman

, Trajano

, Vieira

. Interpreting Signal Amplitudes in Surface Electromyography Studies in Sport and Rehabilitation Sciences. Frontiers in Physiology. 2018;8(1):1–15.

19.

Sergio Fuentes del Toro, Is the Use of a Low-Cost sEMG Sensor Valid to Measure Muscle Fatigue? Sensors. 2019;19, 3204.

20.

Sergio Fuentes del Toro, Validation of a Low-Cost Electromyography (EMG) System via a Commercial and Accurate EMG Device: Pilot Study Sensors. 2019;19, 214.

21.

Patil

, Patil

, Gunjawate

, Rakate

. Low-cost automation for manufacturing of conveyor chain bushes. IOSR Journal of Engineering. 2013;3(12):1–6.

22.

Kihlman

, Ossbahr

, Engström

, Anderson

. Low-cost automation for aircraft assembly. SAE Technical Paper Series 2004.

23.

Groover

. Automation, Production Systems & Computer Integrated Manufacturing. Pearson. 2013;1(20):580–83.

24.

Habib

. Biomimetics: innovations and robotics. International Journal of Mechatronics and Manufacturing Systems. 2011;4(2):113.

25.

Dwarkanath

. Low-cost automation. National Productivity Council of India Training Manual 2013.

26.

Candelas

, García

, Puente

, Pomares

, Jara

, Péerez

, Torres

. Experiences on using arduino for laboratoryexperiments of automatic control and robotics, IFAC-PapersOnLine. 2015;48(29):105–110.

27.

Saraf

, Sadaiah

. Application of artificial intelligence for the prediction of undercut in photochemical machining. International Journal of Mechatronics and Manufacturing Systems. 2013;6(2):183.

28.

Daundkar

, Savant

. Low-cost automation solution for paper bag production using commodity hardware. IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology. 2016;1, 649–652.

29.

Johansson , Malin

, Rissanen , Ritva . Interventions for Return to Work Following Work-related Injuries Among Young Adults: A Systematic Literature Review. Work IOS Press. 2021;795–806.

30.

Van Hees , Suzanne

G.M.

et al. Understanding Work Participation Among Employees with Common Mental Disorders: What Works, for Whom, Under What Circumstances and How? A Systematic Realist Review Protocol. Work IOS Press 202, 827–838.

31.

Kadri Filho , Fauzi

et al. Musculoskeletal Symptoms, Psychosocial Factors and Work Ability in Brazilian Labor Justice Workers. Work IOS Press. 2021;917–926.

32.

Jadhav

, Arunachalam

, Salve

. Ergonomics and efficientworkplace design for hand-sewn footwear artisans in Kolhapur India. Work. 2020;66, 849–860.

33.

Salve

, Jadhav

. Analysis of posture adopted by female Kolhapurichappal (footwear) manufacturing artisans India. Advancesin intelligent systems and computing. Springer. 2018;826, 278–286.

34.

Salve

, Jadhav

, Shete

. Design solution of shoesole (base of the footwear) preparation in traditional handsewn footwear manufacturing: a case study on KolhapuriChappal. Advances in ergonomics in design, Springer. 2017;588, 995–1013.

35.

Jadhav

. Arunachalam

, Salve

Musculoskeletal problems ofhand-sewn crafted footwear manufacturing artisans in Kolhapur,India. Int Arch Occup Environ Health 2021 https://doi.org/10.1007/s00420-021-01734-7

36.

Shinde , Gurunath , Ganesh Jadhav , Amit Kanunje , SM. Sawant Work assessment during assembly process by rapid analysis methods. In International Ergonomics Conference (IIT Guwahati). 2014 420-423.