Assessing the effects of lean on occupational health and safety in the Ready-Made Garment industry

Abstract

BACKGROUND:

Garment manufacturers have been adopting lean manufacturing in order to increase productivity and competitiveness. However, the effects of lean on occupational health and safety (OHS) of the workers are not clear. In the literature, there is an ongoing debate about whether lean and OHS are complementary or contradictory.

OBJECTIVE:

The goal of this study was to contribute to the knowledge base about the relationship between lean and OHS in garment manufacturing.

METHODS:

The study follows an action research methodology including an intervention aimed at improving productivity and OHS in six garment manufacturers in Bangladesh. Both quantitative and qualitative methods were used for investigating the effect of lean tools on productivity and subsequently on OHS.

RESULTS:

We observed instances of improvements of OHS related to the application of three lean tools (VSM, 5 S, Time and Motion Study) in the factories. Furthermore, our results do not indicate negative health effect on workers’ short-term muscular pain, but rather show a statistically significant improvement of workers’ health.

CONCLUSIONS:

The results suggest that it is possible to apply lean without adverse effects for workers, if OHS risks are taken into consideration. However, possible long-term effects on workers’ health need to be further investigated.

Keywords

Apparel productivity ergonomics repetitive strain injuries Bangladesh

1 Introduction

In the manufacturing sector, the focus has been on operational outcomes such as cost, quality, delivery, dependability, and flexibility [1]. Occupational health and safety (OHS) has traditionally not been high on the priority list of performance outcomes. One of the main reasons may be the difficulty in determining the financial consequences of improving OHS conditions, and thereby showing a quantitative relationship between OHS and productivity. The consequence of the exclusive focus on operational priorities is often that organizations push for performance increases in operations even at the cost of the health and safety of the workers [2].

In the last 30 years, companies from various sectors and geographies have used lean manufacturing principles (colloquially known as ‘lean’) as a framework to improve operational performance. Lean has also reached the ready-made garment (RMG) industry due to tough price competition, increased quality requirements, and the frequent changes of business requirements. The international fashion industry now requires smaller lots, increased variety of products, and shorter lead-time for delivery [3, 4]. The core feature of lean is elimination of waste, which has been applied more frequently in the production domain. However, there are indications in the literature that elimination of waste and streamlining the processes in a company can have adverse effects on the health and safety of workers [5]. These adverse effects are often reported in a repetitive assembly context where lean tends to have a negative effect on workers’ physical health [6]. The effects of lean on OHS seem to depend extensively on the content, context, and the process of lean implementation [7, 8].

In general, the relationship between lean and OHS is not completely understood, and that is particularly the case for the ready-made garment (RMG) industry. The garment industry fits the characteristics of a labour intensive and manual assembly of work well, where the literature suggest both physical and mental health risks for the workers. To date, knowledge about the consequences for OHS of lean application in RMG is very limited and inconclusive [9 –11]. There is on the one hand a possibility of intensifying work with a risk of long-term repetitive strain injuries, and on the other hand possibilities for improving workstation design, which may improve workers’ health. However, a recent review concludes that more research is needed, but also point out that although there are examples of studies with negative effects, few studies point towards possibilities for positive effects of lean [12].

The aim of this paper is to narrow this gap in the literature by investigating the effects of lean implementation on OHS in the garment industry in Bangladesh. An action research project was used to introduce lean and integrated OHS elements into six RMG factories and measure before and after results. The findings of this study contributes to the literature by showing that - contrary to the expectations reported in the literature – lean can have positive effects on productivity and OHS outcomes in the garment industry, depending on the content and process of lean implementation. Our results thereby support the literature suggesting [13, 14] that by improving efficiency and simultaneously taking consideration OHS into consideration, then lean implementation is more likely to create synergies between productivity and OHS conditions. However, the physical health effects of long term exposure to sewing work organized based on lean principles still need to be further investigated.

2 Background

RMG is one of the most labor-intensive manufacturing industries, which has motivated international garment manufacturers and brands to outsource their production in countries where cheap labor is available in abundance. Nowadays, China is the largest supplier of RMG followed by other Asian countries such as Bangladesh, India, Laos, Vietnam, Indonesia, and Sri-Lanka. These countries share some common characteristics including cheap labor availability, a growing economy, and poor working conditions [15, 16].

In recent years, the garment sector has focused on competitive dimensions such as productivity and quality in order to attract international buyers [17]. For this reason, most of the garment manufacturers have adopted different strategies to improve productivity, with varying degrees of success [18, 19]. In particular, garment suppliers have frequently adopted lean manufacturing tools and practices to improve productivity and quality, and reduce costs [3 , 21]. However, OHS has gained importance in the wake of deadly accidents in the garment industry, including the Rana Plaza tragedy in Bangladesh. As a consequence, the pressure on garment manufacturers has intensified as international buyers have demanded acceptable OHS conditions for workers as pre-requisite before placing orders [22, 23]. As such, lower cost alone is no longer a sustainable strategy for garment suppliers, who also have to invest in the improvement of OHS conditions in order to attract international brands.

Since the mid-2000 s, the garment manufacturers in several countries like China, Bangladesh, Sri Lanka, India, Pakistan in Asia started to implement lean tools for increasing efficiency and reducing costs. The experiences from introducing lean practices, in most cases, suggest improved productivity [3 , 24–27], but there are also studies showing constraints and more limited effects [12 , 28].

The literature about lean and OHS reports mixed results [6 , 30]. For work that is complex and requires higher skills, the evidence suggests that lean can improve OHS; whereas the opposite is the case for manual assembly work with a tendency for adverse musculoskeletal health effects reported. The theory is that lean can intensify work by increasing work speed and removing micro breaks that are necessary for muscle recovery [5, 31]. It is well established that repetitive work is a risk factor for development of repetitive strain injuries (RSI) [32, 33], and the repetitive tasks of RMG sewing machine operators carry a high risk for RSI [34 –36]. Arguably, the risk of RSI increases as a consequence of lean application; however, lean may also improve the ergonomic arrangement of workstations, reduce the load of equipment and materials, and remove obstacles for causing muscular strain [3, 37] such as excess inventory between the workstation causing unnecessary stretching and bending during frequent pickup.

Table 1
Sample description and pilot line information

Factory Product of this factory Production Pieces/month Number of workers Pilot Line information* Experience with Lean

F-1 T- shirt, Polo shirt, Jacket, Female top wear 900,000 3,450 37 Workstation; Product: T-shirt, Polo shirt; Gender: M = 30%; F = 70%, Mean worker age: 24 y. The factory has industrial engineers (IE) with limited lean experience (5 S)

F-2 Reversible jacket, Shirt, T- shirt, Polo shirt, Jersey 600,000 850 30 Workstation; Product: T- shirt, Polo shirt; Gender: M = 35%; F = 60%, Mean worker age: 22 y. The factory has experienced IE and started using basic lean tools

F-3 T-shirt, Pant, Polo shirt, Dresses, Baby wear 1050,000 2,949 24 Workstation, Product: T-shirt, Pant; Gender: M = 30%; F = 70%, Mean worker age: 24 y. The factory has experienced IE with basic lean experience

F-4 T-shirt, Polo shirt, Tank top 3000,000 6,000 27 Workstation, Product: T-shirt, Polo shirt; Gender: M = 30%; F = 70%, Mean worker age: 23 y. The factory has experienced IE and started to implement some lean tools

F-5 Dress, Noos top, T-shirt, Polo shirt 360,000 1,200 53 Workstation; Product: T-shirt, Noose top; Gender: M = 40%; F = 60%, Mean worker age: 22 y. The factory has IE with limited lean experience (5 S)

F-6 T-shirt, Polo shirt, Sweatshirt, Tops 300,0000 14,690 21 Workstation; Product: T-shirt, Polo shirt; Gender: M = 30%; F = 70%, Mean worker age: 21 y. The factory has experienced IE and started to implement lean tools

Factory	Product of this factory	Production Pieces/month	Number of workers	Pilot Line information*	Experience with Lean
F-1	T- shirt, Polo shirt, Jacket, Female top wear	900,000	3,450	37 Workstation; Product: T-shirt, Polo shirt; Gender: M = 30%; F = 70%, Mean worker age: 24 y.	The factory has industrial engineers (IE) with limited lean experience (5 S)
F-2	Reversible jacket, Shirt, T- shirt, Polo shirt, Jersey	600,000	850	30 Workstation; Product: T- shirt, Polo shirt; Gender: M = 35%; F = 60%, Mean worker age: 22 y.	The factory has experienced IE and started using basic lean tools
F-3	T-shirt, Pant, Polo shirt, Dresses, Baby wear	1050,000	2,949	24 Workstation, Product: T-shirt, Pant; Gender: M = 30%; F = 70%, Mean worker age: 24 y.	The factory has experienced IE with basic lean experience
F-4	T-shirt, Polo shirt, Tank top	3000,000	6,000	27 Workstation, Product: T-shirt, Polo shirt; Gender: M = 30%; F = 70%, Mean worker age: 23 y.	The factory has experienced IE and started to implement some lean tools
F-5	Dress, Noos top, T-shirt, Polo shirt	360,000	1,200	53 Workstation; Product: T-shirt, Noose top; Gender: M = 40%; F = 60%, Mean worker age: 22 y.	The factory has IE with limited lean experience (5 S)
F-6	T-shirt, Polo shirt, Sweatshirt, Tops	300,0000	14,690	21 Workstation; Product: T-shirt, Polo shirt; Gender: M = 30%; F = 70%, Mean worker age: 21 y.	The factory has experienced IE and started to implement lean tools

* M = Male; F = Female (Most workers had short seniority from a few months up to five years and very few more than five years).

Lean manufacturing consists of a wide range of tools [38] such as value stream mapping, 5 S, SMED and Kaizen, which may have varying effects on OHS and productivity. It is not expected that lean has one general effect on OHS. The effect on OHS outcomes will probably depend on both context and the mix of lean tools as suggested in the literature [8].

3 Methodology

This study was designed as an action research project with interventions to introduce change in real life situations [39, 40]. Action research methodologies have also been widely used in OHS [41, 42] intervention research. Action research is especially relevant to study real life changes, which are highly context dependent. Susman and Evered [43] have developed an often used five step model for action research: 1) diagnosing, 2) action planning, 3) action taking, 4) evaluation, and 5) specifying learning. In this study, action research was used to introduce and test lean implementation with integration of OHS consideration. The target group was garment factories in Bangladesh and the effects of the integrated lean implementation on productivity and OHS were measured and assessed. The first and the final steps were carried out by the researchers. Before the intervention, the researchers developed an intervention manual [44], corresponding to the diagnosing in action research, which outlined the methodology to introduce change based on integrated lean in the garment companies. The development of the manual was based on a review of the literature related to study of productivity and OHS improvement [12].

3.1 Company selection

The sample includes six garment factories in Bangladesh. Snowball sampling was used to select factories that met the following criteria: 1) top management committed to supporting the change (pressure from buyers side was one of the ways to secure the commitment of the factories); 2) export-focused with sewing basic ready-made garments as the main activity; 3) availability of one production line for lean intervention (pilot line); 4) producing the same type of basic garments (basic T-shirt and polo T-shirts).

Table 1 presents the basic information of the six factories including type of products, production volume in pieces/month, number of workers, pilot line information (number of workstations, number of workers, product types, male/female percent, average age of workers), and experience with lean.

3.2 Intervention procedure

The intervention included the three action research steps: 1) action planning; 2) action taking; and 3) evaluation.

Action planning: This step started with an introductory phase, where the team presented the project to each factory’s management at an introductory meeting, where expectations and commitments from both sides were discussed and aligned. It was agreed with management to establish a core management team, which is responsible for the overall supervision and an operational team with the responsibility to carry out tangible changes. The operational teams included Industrial Engineers (IE), production managers, quality managers, human resource and compliance managers, as well as line supervisors and workers representatives. One production line was selected as a pilot for the implementation of lean in each factory. Based on the outcomes of the introductory meeting, the researchers assessed the factory’s knowledge of lean processes and OHS, and then organized training focused on lean tools and OHS in order to raise the capabilities of the team members in the factory. Building of capacity involved formal and on-the-job training. The formal training included four modules covering lean theory and philosophy, the practical tools such as Value Stream Mapping (VSM), 5 S, Time and Motion Study (TMS), workstation design, ergonomics, and OHS.

The second part of the action planning was collection of the baseline data from the pilot line to make a focused plan for the start of lean implementation. Data about productivity covered TMS, efficiency, value added ratio, and 5 S (Sort, Set in order, Shine, Standardize, and Sustain) score. Based on literature [26 , 37], researcher prepared an audit sheet for 5 S specially focused on sewing floor, and scores was given on the existing conditions of the sewing floor. This audit sheet is containing proper labeling of input rack; making the aisle and obstacle free like cartons and idle machine; setting the various parts and accessories in order in the sewing table; removing all the unnecessary items like previous styles garments, thread, cones, trim card etc.; status of all required documents like measurement sheet, trim card, index sheet etc.; loose and open electric wire; broken plug and sockets; floor area is neat and clean and free from waste etc. in the sewing floor. Data about OHS covered work postures, workstation design, and workers health assessment. The baseline data measurements were collected jointly by members of the factory operational team and the researchers. The results of the baseline study were used to identify possibilities for improvements in collaboration between the researchers and the management.

Action taking: The actual change process was tailored to each factory depending on needs and priorities and implemented by each factory’s operational teams supported by the researchers. All factories worked with improvements related to VSM, time and motion study, 5 S, and lean flow to identify possibilities for improvements including both productivity and OHS improvements.

Evaluation: The intervention process was completed by evaluation of the effects which included measurements of Key Performance Indicator (KPI). The measurements were used to compare before and after, and the results of the evaluation were subsequently used for feedback to the companies. The whole intervention process was carried out from December 2017 to July 2018.

3.3 Data collection

Data collection included pre- and post- measurement of productivity and OHS performance measures. Table 2 gives an overview of the data collected.

Table 2
Tools and overview of data collection

Tools Overview of Data collection

Time and motion studies (TMS) Measurement of task time. Photos and videos for all tasks and steps in production process with identification of bottlenecks.

5 S audit (including OHS assessment) The assessment included unnecessary items (unused machines, previous thread, products from previous orders), transport area, workstation design (easy reach, elbow height, make some new tools etc.), labels, signs and color coding, regular maintenance and cleanness, and availability of toolbox and standard operation procedures. All the parameters were assessed on a score from one to five. Photos were taken before and after 5 S implementation.

Value stream mapping (VSM) Calculation the percentage of value added and non-value-added time in the process: One piece of product is marked and followed from start to finish (final product).

Survey of worker pain and fatigue A simple instrument based on the validated instrument of Corlett Bishop body chart (50). The survey contains 10 questions assessed by all workers in the production line on a three-point scale (always (2), sometimes (1), and never (0)). The questions include musculoskeletal pain and fatigue, neck, buttock, upper and lower arm, upper, mid and lower back, thighs, legs and shoulder. The researchers assisted workers in filling the questionnaire.

Qualitative interviews Interviews with management, supervisors, and workers were carried out in all factories

Tools	Overview of Data collection
Time and motion studies (TMS)	Measurement of task time. Photos and videos for all tasks and steps in production process with identification of bottlenecks.
5 S audit (including OHS assessment)	The assessment included unnecessary items (unused machines, previous thread, products from previous orders), transport area, workstation design (easy reach, elbow height, make some new tools etc.), labels, signs and color coding, regular maintenance and cleanness, and availability of toolbox and standard operation procedures. All the parameters were assessed on a score from one to five. Photos were taken before and after 5 S implementation.
Value stream mapping (VSM)	Calculation the percentage of value added and non-value-added time in the process: One piece of product is marked and followed from start to finish (final product).
Survey of worker pain and fatigue	A simple instrument based on the validated instrument of Corlett Bishop body chart (50). The survey contains 10 questions assessed by all workers in the production line on a three-point scale (always (2), sometimes (1), and never (0)). The questions include musculoskeletal pain and fatigue, neck, buttock, upper and lower arm, upper, mid and lower back, thighs, legs and shoulder. The researchers assisted workers in filling the questionnaire.
Qualitative interviews	Interviews with management, supervisors, and workers were carried out in all factories

Baseline measurements were carried out January-March 2018 and post-measurements were carried out May-July 2018. Numerical production measures were calculated and compared before and after the application of lean tools [45]. Efficiency was calculated based on the standard procedure for RMG [46].

3.4 Data analysis

The survey data were imported into SPSS v 25.0. Participants score of pain and fatigue were analyzed using descriptive statistics, and paired sample t- tests for pre- and post- measurement of survey results in all body parts. The qualitative data were used to follow up on the numerical data and increase the understanding of the implementations and impact of lean on productivity and OHS measures.

4 Results of intervention

4.1 Lean tools

The changes related to the application of the three lean tools (VSM, 5 s, Time and Motion study) and the main actions implemented by the factories are reported below. Table 3 presents the change in the percent of value-added time after the intervention.

Table 3
Change in value added time and the main actions of improvement

Factory VSM (Percentage of value added in total cycle time) Main actions of improvement

Before (%) After (%) Change (%) Bundle size reduction Cell formation by job sharing/merging Quality control done by operator Keeping extra bobbin in the workstation Supply auxiliary machine tools Control of work in process (WIP) between workstations

F-1 3.3 4.7 42 X X X X

F-2 2.5 4.5 80 X X X X X

F-3 3.0 4.0 33 X X

F-4 2.0 3.0 50 X

F-5 1.0 2.0 100 X X X X X

F-6 2.0 2.0 0 X X

Factory	VSM (Percentage of value added in total cycle time)	Main actions of improvement
F-1	3.3	4.7	42	X	X	X	X
F-2	2.5	4.5	80	X	X	X	X	X
F-3	3.0	4.0	33	X	X
F-4	2.0	3.0	50	X
F-5	1.0	2.0	100	X	X	X	X	X
F-6	2.0	2.0	0	X	X

Table 5

Change in efficiency and the main actions of improvement

Factory	Efficiency percentage (%)			Main actions of improvement
Before (%)	After (%)	Change (%)	Operators sewing skills	5S	Reducing unnecessary activities	Quality control done by operators	Rearranging workstation	Reducing/adding helper	Keeping bundle on thigh	Attaching box in the workstations	Cell formation	Adjustable Chair
F-1	34	39	14.7	X	X	X	X
F-2	50	63	26.0	X	X	X	X	X	X	X	X
F-3	51	58	14.9	X	X	X	X	X	X	X	X
F-4	61	66	8.2	X	X	X
F-5	79	81	2.5	X	X	X	X	X
F-6	76	80	5.3	X	X	X	X	X	X	X

Five of the six factories increased the value-added time whereas the last one remained unchanged. The three main factors for the improvements were bundle size reduction, quality control done by workers, and control of work in progress (WIP) between workstations. As for bundle size, this action focused on the reduction of bundle size of garments, which most often ranged from 20–30 pieces and resulted in long time for processing the whole bundle. Large bundles required unnecessary stretching, bending, and twisting, because they were heavy and difficult to pick up and drop between workstations. The action resulted in smaller bundles of 10–15 pieces. Moreover, the WIP was reduced, which helped improve visibility between workstations as less materials and unfinished products were placed between machines and on the floor reducing the risk of accidents. Factories F2 and F5 achieved the highest improvement, because they implemented a full range of actions (i.e. cell formation, keeping an extra bobbin in the workstation, and supplying some additional hand tools). Factory F6 implemented two main actions (quality control done by operators and control of WIP between workstations); however, the results did not materialize as the plant had frequent problems due to power failure and the power generator could not supply the needed power to run the production smoothly.

Table 4 presents the difference and percentage change in 5 S scores after the intervention and the main actions for improving 5 S in the production line.

Table 4

Change in 5S score and the main actions of improvement

Factory	5S score change in percentage (%)			Main actions of improvement
Before (%)	After (%)	Change (%)	Standardized tool storage system	Removing unnecessary items	Redesigning workstations	Visual management tool	Cleaning workstations	Labelled input/output rack	Keeping racks and bins in specified place
F-1	55	62	12.7	X	X	X	X	X
F-2	58	71	22.4	X	X	X	X	X	X	X
F-3	55	67	21.8	X	X	X	X	X
F-4	68	75	10.3	X	X	X	X
F-5	70	85	21.4	X	X	X	X	X	X
F-6	55	63	14.5	X	X	X	X	X

The main four actions for improving 5 S in the factories are standardized tool storage system, removing unnecessary items, redesigning workstations, and cleaning workstations. Removal of unnecessary items covered typically removal of torn-out belt covers, broken needle guards, garments leftovers, old garment thread cones, and other small equipment that are not used in the production. Elimination of these unnecessary items saved place and increased visibility. As for redesign/rearranging workstations, the necessary items were set in order and put in the right place, so that workers do not spend extra time or make extra movements to pick the necessary items. For example, before the redesign and rearranging of workstations, operators of some workstations used to keep the different types of labels in one place, which caused much delay in sorting and picking the right label. F2 achieved the highest increase in 5 S score because the factory implemented a full range of actions for improvement (including “keeping racks and bins in specified place”). F1 and F4 had increased below the level of the other plants. These two factories faced problems related to the redesign of workstations and the rearrangement of input and output area due to shortage of available space.

Table 5 presents an overview of the change in efficiency for the six factories and the main actions for improvement. All the factories achieved improvements in efficiency ranging from 2.5% to 26%. The most widely applied actions for improvement of efficiency are training operators in sewing skills, applying 5 S principles, reducing unnecessary activities, and quality control done by workers. The overall results seem to be related to management support, which was particularly strong in F2; whereas, there was a low level of management commitment in F5. The highest efficiency increase was achieved in F-2 and it is the only factory that implemented cell formation. In cellular manufacturing, job sharing is used to increase efficiency as workers’ capacities are balanced when workload is shifted from overloaded to idle workers. The three factories with larger increases in efficiency also rearranged workstations to secure materials and equipment within easy reach; in addition to the above action, F-3 provided adjustable chairs.

Details about the main actions for improvement of efficiency are presented in Table 6. The changes presented in the table were mainly initiated by TMS and targeted the bottleneck. They constituted relatively small and very focused changes in the sewing and related operations, with time savings of only 2–11 seconds in cycle time, but the consequences for efficiency are relatively large as they reduced the bottlenecks.

4.2 Assessment of OHS (pain and fatigue survey)

The participants score of pain and fatigue is affected by the range of actions implemented during intervention. In addition to the actions related to VSM, 5 S, and Time and Motion study, the factories implemented awareness programs for ergonomic safety, physical exercises during work hours, and training related to correction of body posture. Table 7 shows descriptive statistics of participant scores of pain and fatigue for the six factories including all workers in the pilot production line.

Table 8 shows that the pain and fatigue index was reduced for all factories after the intervention. The pre-intervention levels vary between the six factories. A paired t test showed that pain and fatigue index was reduced significantly in all factories where p^* value (p* < 0.05) is significant as a result of training received during intervention (see Table 8). Improvement scores were calculated by subtracting scores on the before and after participant score of pain and fatigue.

Table 6
Main actions for efficiency increase in the six factories

Factory Change in tasks and operations Range of time saving/cycle Increased capacity per hour (%)

F-1 Handling system of garments modified: the sewing burst increased. 6 second 5

F-2 Cell formation includes job sharing where capacity is balanced between workers. Side seam operation: It was recommended to hold the two parts tightly to avoid mismatch and keeping bundle on thighs instead of side table. 11 second 32

F-3 In back panel tack operation, workers are trained to do work more precisely and reduce extra movement by using adjustable chair. 5 second 18

F-4 Operator used to secure matching of different parts of garment before stitching. It was time consuming and operator had to stop 3- 4 times. A helper was assigned to mark the garments, which saved the operator time. As consequence, the operator could do the stitching without stopping. 7 second 24

F-5 Bottom frill tuck improved by increasing worker skills and changing the pick-up location 2 second 2

F-6 Labelling pickup improved by attaching a box into the machine table, which facilitated pickup of labels and reduced pickup time. 5 second 2

Factory	Change in tasks and operations	Range of time saving/cycle	Increased capacity per hour (%)
F-1	Handling system of garments modified: the sewing burst increased.	6 second	5
F-2	Cell formation includes job sharing where capacity is balanced between workers. Side seam operation: It was recommended to hold the two parts tightly to avoid mismatch and keeping bundle on thighs instead of side table.	11 second	32
F-3	In back panel tack operation, workers are trained to do work more precisely and reduce extra movement by using adjustable chair.	5 second	18
F-4	Operator used to secure matching of different parts of garment before stitching. It was time consuming and operator had to stop 3- 4 times. A helper was assigned to mark the garments, which saved the operator time. As consequence, the operator could do the stitching without stopping.	7 second	24
F-5	Bottom frill tuck improved by increasing worker skills and changing the pick-up location	2 second	2
F-6	Labelling pickup improved by attaching a box into the machine table, which facilitated pickup of labels and reduced pickup time.	5 second	2

5 Discussion

The aim of the study was to assess the effects of lean manufacturing processes on OHS outcomes in the garment industry in Bangladesh. We discussed the assessment from two different perspectives. The first one is related to the changes in the experience of musculoskeletal pain and fatigue, and the second is related to changes in work design associated with lean implementation.

For musculoskeletal pain and fatigue, workers have generally experienced reduction in pain intensity. This quick reduction in pain, after only few months of intervention, may be surprising. There can be several explanations. One explanation can be supported by the young age of workers and the short exposure time. It can therefore be expected that most musculoskeletal pain has an acute character and changes can appear after relatively short time; but it is important to emphasize that the result do not provide information about chronic pain and thereby long-term exposure to work organized after lean methodologies.

Another explanation can be the so-called “Hawthorne effect” [47], which may have contributed to the improvement. This effect indicates that social attention is a positive experience for workers, which by itself may improve well-being. In this case the workers experienced for the first-time extensive attention from both management and researchers, and this attention may have positively affected the outcome. Yet, perhaps the most important interpretation of this result is that the lack of any tendency of adverse health effects of lean does not support the literature suggesting adverse effects in manual assembly work [7]. Furthermore, the results thereby indicate that the application of basic lean tools such as TMS, 5 S, and VSM might have a positive effect on the acute experience of musculoskeletal pain and fatigue. It is still a question, however, whether the different tools as well as the different tangible changes of the work had different effects on OHS.

The other part of the assessment is a comparison of the most used improvement actions associated with the specific lean tool(s) and the likely impact on OHS for each of the actions (see Table 9).

Table 7
Descriptive Statistics for participants score of pain and fatigue

Pair Factory (F) Mean Std. Deviation Number of workers (N)

Pair 1 F1B 8.03 4.86 37

F1A 6.08 2.45 37

Pair 2 F2B 5.10 2.60 30

F2A 3.57 2.14 30

Pair 3 F3B 5.46 3.26 24

F3A 4.58 2.80 24

Pair 4 F4B 5.11 3.91 27

F4A 4.11 3.20 27

Pair 5 F5B 1.72 2.57 53

F5A 1.13 2.57 53

Pair 6 F6B 8.29 5.18 21

F6A 5.52 4.01 21

Pair	Factory (F)	Mean	Std. Deviation	Number of workers (N)
Pair 1	F1B	8.03	4.86	37
	F1A	6.08	2.45	37
Pair 2	F2B	5.10	2.60	30
	F2A	3.57	2.14	30
Pair 3	F3B	5.46	3.26	24
	F3A	4.58	2.80	24
Pair 4	F4B	5.11	3.91	27
	F4A	4.11	3.20	27
Pair 5	F5B	1.72	2.57	53
	F5A	1.13	2.57	53
Pair 6	F6B	8.29	5.18	21
	F6A	5.52	4.01	21

Note: B = Score before Intervention; A = Score after Intervention

Table 8

Pairwise comparison (t-test) for participants score of pain and fatigue before and after lean intervention

Paired differences
Pair	Factory	Number of	Mean	Std.	95% Confidence		t	Sig.
workers	Deviation	Interval of the difference		(2-tailed)
(N)	Lower	Upper	p^*
Pair 1	F1B - F1A	37	1.95	5.25	0.19	3.70	2.25	0.030
Pair 2	F2B - F2A	30	1.53	3.01	0.41	2.66	2.79	0.009
Pair 3	F3B - F3A	24	0.88	1.62	0.19	1.56	2.64	0.015
Pair 4	F4B - F4A	27	1.00	1.64	0.35	1.65	3.17	0.004
Pair 5	F5B - F5A	53	0.58	0.97	0.32	0.85	4.39	0.000
Pair 6	F6B - F6A	21	2.76	5.88	0.08	5.44	2.15	0.044

Note: Significant value p^* < 0.05.

Table 9

Actions, Lean tools, assessment of OHS consequences and the reason for assessment

Action in the sewing pilot line	Applied lean tools	Assessment of OHS consequences	Reason for assessment
Bundle size reduction	VSM	+	Easier pickup and drop of material resulting in fewer awkward work movements (bending, twisting and stretching)
Keeping extra bobbin in the work station	VSM	0	Reduce extra movement for picking up bobbin from another place
Supply auxiliary machine tools	VSM	0	Auxiliary tools are time saving and increase the quality of work (more precision)
Control of work in process (WIP) between workstations	VSM	+	Increase visibility, facilitate picking and dropping of bundles
Standardized tool storage system	5S	0	Facilitate pick up of necessary items
Removing unnecessary items	5S	+	Create more space (easy movement), increase visibility and reduce risk of accident
Redesigning/rearranging workstations	5S, TMS	+	Facilitate pickup and drop of bundles before and after completing work. Improve work postures and movements
Adjustable Chair	5S	+	Improve sitting positions with support and adjustment to body size
Cleaning workstations	5S	+	Keep workstations and shop floor clean and free of dust reduce the risk of respiratory exposure and accidents
Labelled input/output rack	5S	0	Labelling helps to identify the flow of WIP more easily
Keeping racks and bins in specified place	5S	+	Reduce risk of accident
Operators sewing skills	TMS	+	Reduces, exertion in performing work task
Removing unnecessary activities	TMS	0 or –	Depending on the task, removing similar task will have a neutral effect, but there may be a tendency to less variation
Quality control done by operator	TMS	+	Increase job variation
Reducing/adding helper	TMS	+ or –	Depending on the actual change, reducing helper may create overload of tasks, but also create more variation of tasks. Adding helper may reduce overload, but also create less variation
Keeping bundle on thigh	TMS	+	Reduce stretching, twisting and bending
Cell formation by job sharing/ merging	TMS	+	Increase multi-skilling and increase variation

Note: Positive (+); Negative (–), Neutral (0).

The assessment indicates that most of the tangible changes are likely to have either a positive or a neutral effect on OHS. Some changes may not only have a positive ergonomic effect but also reduce other risk factors such as accidents and dust. As for VSM and 5 S, they do not seem to have indications of adverse effects, whereas for time and motion studies the effects can be more ambiguous. TMS has roots back to basic industrial engineering [48] and has usually been associated with repetitive strain injuries [35]. But TMS is at the same time a basic key tool for standardization and removal of waste, which is a key element of lean. Some related changes have a relatively straightforward potential for reducing risks such as training operators and adding quality control. Other actions may depend on the specific design of the changes, such as reducing/adding a helper and removing unnecessary activities.

In the evaluation of the consequences of lean in this study, the integration of with OHS must also be taken into consideration. Both management, operational team and workers were trained in OHS with a special focus on ergonomics, and it is therefore likely that lean implementation without explicit consideration of OHS might have less positive outcomes.

It is furthermore important to consider the total results of the changes. Although the acute musculoskeletal pain and fatigue seem to be reduced as an indication of the overall effect, there may be effects of long term exposure related to the so-called “the ergonomic trap” [49]. This concept is especially relevant for repetitive manual work such as sewing, and points to possibility of ergonomic improvements making the work easier, and thereby opening the possibility for increasing speed and intensity of the work. Increasing intensity of work might in turn result in long-term exposure and chronical health problems. This is particularly valid when plant management increases production targets as consequence of increased workers’ capacity. Worker involvement can be a tool to control this problem, but it is in particular difficult in a country like Bangladesh where the unions are weak.

One consequence of this possible health risk is the need for further research. Research in the relations between lean and health does at the move not provide any information about the health effects of long-term exposure to lean. Therefore, it is pertinent to carry out studies of the consequences of long-term exposure to lean in RMG, especially studies related to chronical repetitive strain injuries. Such studies need to go hand in hand with in-depth studies on the use of the different lean tools and the resultant design of the work. This study has started disentangling the effects and found that there is not one uniform effect of lean. Rather, the effects of lean implementation are embedded in many small specific changes, which may have different effects on workers’ health and well-being. It therefore needs to be tested in new studies whether the assessment of the specific changes can be repeated in other factories and in other countries.

6 Conclusion

Contrary to some expectations in the literature, our results do not indicate any overall negative OHS effects of application of basic lean tools in the six RMG factories. Rather, the tendency is towards improved health for the workers. However, it is important for the interpretation of this finding that OHS was given an explicit priority during lean implementation.

More research is needed to confirm these results and to learn about the possible health effects for workers after long term exposure to work organized after lean methodologies. For practitioners, the findings imply that implementation of basic lean tools with careful consideration of OHS can be a way forward to increase productivity competitiveness without jeopardizing compliance demands from buyers, but also that worker involvement is important to protect the workers from a potential health risk.

Conflict of interest

None to report.

Footnotes

Acknowledgement

This study is part of the productivity and occupational health and safety (POHS) project which is four-year project funded by the Danish Ministry of Foreign Affairs with the collaboration between Aalborg University (Denmark) and Ahsanullah University of Science and Technology (Bangladesh).

References

Ward

, Duray

, Keong Leong

, Sum

C-C

, Leong

, Sum

C-C

. Business environment, operations strategy, and performance: An empirical study of Singapore manufacturers. J Oper Manag. 1995;13(2):99–115.

Von Thiele Schwarz

, Hasson

, Tafvelin

. Leadership training as an occupational health intervention: Improved safety and sustained productivity. Saf Sci. 2016;81:35–45.

Marudhamuthu

, krishnaswamy

, Pillai

. The Development and Implementation of Lean Manufacturing Techniques in Indian garment Industry. Jordan J Mech Ind Eng. 2011;5(6):527.

Kader

, Akter

MKM

. Analysis of the Factors Affecting the Lead Time for Export of Readymade Apparels From Bangladesh; Proposals for Strategic Reduction of Lead Time. Eur Sci J. 2014;10(33):268–83.

Westgaard

, Winkel

. Occupational musculoskeletal and mental health: Significance of rationalization and opportunities to create sustainable production systems - A systematic review. Appl Ergon. 2011;42(2):261–96.

Brännmark

, Håkansson

. Lean production and work-related musculoskeletal disorders: Overviews of international and Swedish studies. Work J Prev Assess Rehabil. 2012;41:2321–8.

Hasle

, Bojesen

, Jensen

, Bramming

, Jensen

, Bramming

, et al. Lean and the working environment: A review of the literature. Int J Oper Prod Manag. 2012;32(7):829–49.

Hasle

. Lean Production-An Evaluation of the Possibilities for an Employee Supportive Lean Practice. Hum Factors Ergon Manuf Serv Ind. 2014;24(1):40–53.

Hamja

, Hossain

, Maalouf

, Hasle

A Review Paper on Lean and Occupational Health and Safety In: International Conference on Mechanical Engineering and Renewable Energy (ICMERE2017), Chittagong, Bangladesh; 2017.

10.

Ferdousi

, Ahmed

. An Investigation of Manufacturing Performance Improvement through Lean Production: A Study on Bangladeshi Garment Firms. Int J Bus MAanagement. 2009;4(9):106–16.

11.

Abeysekera

, Illankoon

. The demands and benefits of ergonomicsin Sri Lankan apparel industry: A case study at MAS holdings. Work. 2016;55(2):255–61.

12.

Hamja

, Maalouf

, Hasle

. The effect of Lean on Occupational Health and Safety and productivity in the Garment Industry - A Literature Review. Prod Manuf Res. 2019.

13.

Maalouf

, Hamja

, Hasle

Enabling the creation of synergies between Occupational Health and Safety and Productivity, In: 5th International EurOMA Sustainable Operations and Supply Chains Forum. Kassel, Germany; 2018.

14.

Longoni

, Pagell

, Johnston

, Veltri

. When does lean hurt? - an exploration of lean practices and worker health and safety outcomes. Int J Prod Res. 2013;51(11):3300–20.

15.

Hasnin

, Ahsan

. Employee Training and Operational Risks: The Case of RMG Sector in Bangladesh. World J Soc Sci. 2016;6(2):71–81.

16.

Rakib

, Adnan

. Challenges of Ready-Made Garments Sector in Bangladesh: Ways to Overcome. BUFT J. 2015;3:77–90.

17.

Wickramasinghe

, Wickramasinghe

. Perceived organisational support, job involvement and turnover intention in lean production in Sri Lanka. Int J Adv Manuf Technol. 2011;55(5–8):817–30.

18.

Hodge

, Goforth Ross

, Joines

, Thoney

. Adapting lean manufacturing principles to the textile industry. Prod Plan Control. 2011;22(3):237–47.

19.

Maia

, Alves

, Leão

, Leao

, Leão

. Design of a Lean Methodology for an Ergonomic and Sustainable Work Environment in Textile and Garment Industry. In: Design, Materials and Manufacturing, Amer Soc Mechanical Engineers: Amer Soc Mechanical Engineers; 2012; pp. 1843.

20.

Wickramasinghe

GLD

, Wickramasinghe

. Implementation of lean production practices and manufacturing performance. J Manuf Technol Manag. 2017;28(4):531–50.

21.

Brown

, O’Rourke

. Lean manufacturing comes to China: A case study of its impact on workplace health and safety. Int J Occup Environ Health. 1998;13(3):249–57.

22.

Bulut

, Lane

. The private regulation of labour standards and rights in the global clothing industry: An evaluation of its effectiveness in two developing countries. New Polit Econ. 2011.

23.

Hoque

, Rana

. Buyer-supplier relationships from the perspective of working environment and organisational performance: Review and research agenda. Manag Rev Q. 2019.

24.

Wickramasinghe

, Wickramasinghe

. Effects of perceived organisational support on participation in decision making, affective commitment and job satisfaction in lean production in Sri Lanka. J Manuf Technol Manag. 2012.

25.

Wickramasinghe

, Wickramasinghe

GLD

. Variable pay and job performance of shop-floor workers in lean production. J Manuf Technol Manag. 2016;27(2):287–311.

26.

Hammad Saeed

Shamsi

. 5S Conditions and Improvement Methodology in Apparel Industry in Pakistan. IOSR J Polym Text Eng. 2014;1(2):15–21.

27.

Quddus

, Nazmul Ahsan

AMM

. A shop-floor kaizen breakthrough approach to improve working environment and productivity of a sewing floor in RMG industry. J Text Apparel, Technol Manag. 2014;8(4).

28.

Farhana

Ferdousi

. Lean Production Practices in Bangladesh: An Investigation into the Extent of Practices and the Existence of Enabling Environments for Lean Implementation. University of Wollongong Thesis Collections. University of Wollongong; 2009.

29.

Bouville

, Alis

. The effects of lean organizational practices on employees’ attitudes and workers’ health: Evidence from France. Int J Hum Resour Manag. 2014;25(21):3016–37.

30.

Conti

, Angelis

, Cooper

, Faragher

, Gill

. The effects of lean production on worker job stress. Int J Oper Prod Manag. 2006;26(9):1013–38.

31.

Neumann

, Winkel

, Palmerud

, Forsman

. Innovation and employee injury risk in automotive disassembly operations. Int J Prod Res. 2018;56(9):3188–203.

32.

Muggleton

, Allen

, Chappell

. Hand and arm injuries associated with repetitive manual work in industry: A review of disorders, risk factors and preventive measures. Ergonomics. 1999)714–39.

33.

Buckle

, Jason Devereux

. The nature of work-related neck and upper limb musculoskeletal disorders. Appl Ergon. 2002;33(3):207–17.

34.

Sealetsa

, Thatcher

. Ergonomics issues among sewing machine operators in the textile manufacturing industry in Botswana. Work. 2011;38(3):279–89.

35.

Vezina

, Tierney

, Messing

. When is light work heavy? Components of the physical workload of sewing machine operators working at piecework rates. Appl Ergon. 1992;23(4):268–76.

36.

Ozturk

, Esin

. Investigation of musculoskeletal symptoms and ergonomic risk factors among female sewing machine operators in Turkey. Int J Ind Ergon. 2011;41(6):585–91.

37.

Vijayakumar

, Robinson

. Impacts of Lean Tools and Techniques for Improving Manufacturing Performance in Garment Manufacturing Scenario: A Case Study. Int J Adv Eng Technol. 2016;7(2):251–60.

38.

Ohno

. Toyota Production System [Internet]. Vol. 4, International Journal of Operations. 1988. 3-11 p. Available from: http://books.google.com/books?id=7_-67SshOy8C

39.

Greenwood

, Levin

. Introduction to action research: Social research for social change. Thousand Oaks, Calif.: Sage; 2007.

40.

Nielsen

, Svensson

. Action Research and Interactive Research. Mastricht: Shaker Publishers; 2006.

41.

Hasle

, Jensen

. Changing the internal health and safety organisation through organisational learning and change management. Hum Factors Ergon Manuf. 2006;16(3):269–84.

42.

Neumann

, Ekman

, Winkel

. Integrating ergonomics into production system development - The Volvo Powertrain case. Appl Ergon. 2009;40(3):527–37.

43.

Susman

, Evered

, Susman

G 1

. An Assessment of the Scientific Merits of Action Research. Adm Sci Q. 1978;23(4):582–603.

44.

Maalouf

et al. Strategies and methods for the improvement of Productivity and occupational health and safety in garment factories. Aalborg; 2015.

45.

Institute

lean.org - Lean Enterprise Institute | Lean Production | Lean Manufacturing | LEI | Lean Services; Available from: https://www.lean.org/

46.

Sarkar

. Garment maker’s key performance indicators. Online Clothing Study; 2016.

47.

Kompier

MAJ

. the “Hawthorne effect” is a myth, but what keeps the story going? Scand J Work Environ Heal. 2006;32(5):402–12.

48.

Taylor

. Scientific management. Harper & Brothers: New York; 1911.

49.

O’Neill

. Europe under strain: A report on trade union initiatives to combat workplace musculoskeletal disorders. Sheffield: European Trade Union Technical Bureau for Health and Safety; 1999.

50.

Corlett

, Bishop

. A technique for assessing postural discomfort. Ergonomics. 1976;19(2):175–82.