Streamlining operations management by classifying methods and concepts of Lean and Ergonomics within a sociotechnical framework

Brunner, Stefan; Yuching, Candice Kam; Bengler, Klaus Article — Published Version Streamlining operations management by classifying methods and concepts of Lean and Ergonomics within a sociotechnical framework Operations Management Research Provided in Cooperation with: Springer Nature Suggested Citation: Brunner, Stefan; Yuching, Candice Kam; Bengler, Klaus (2024) : Streamlining operations management by classifying methods and concepts of Lean and Ergonomics within a sociotechnical framework, Operations Management Research, ISSN 1936-9743, Springer US, New York, NY, Vol. 17, Iss. 3, pp. 1172-1196, https://doi.org/10.1007/s12063-024-00488-y This Version is available at: https://hdl.handle.net/10419/315642 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. http://creativecommons.org/licenses/by/4.0/ Vol:.(1234567890) Operations Management Research (2024) 17:1172–1196 https://doi.org/10.1007/s12063-024-00488-y Streamlining operations management byclassifying methods andconcepts ofLean andErgonomics within asociotechnical framework StefanBrunner1 · CandiceKamYuching1· KlausBengler1 Received: 23 October 2023 / Revised: 15 April 2024 / Accepted: 16 April 2024 / Published online: 12 June 2024 © The Author(s) 2024 Abstract Companies have implemented Lean to increase efficiency and competitiveness. However, the importance of Ergonomics is often neglected, resulting in ergonomic problems and lower profitability and acceptance of Lean. This study presents a comprehensive approach to Operations and Production Management (OPM) considering sociotechnical synergies.For Lean and Ergonomics, literature-based main methodologies and categories are defined. These main methodologies/categories are used as search-term combinations in a further literature search. This literature is divided into “Production worker” (PW), “Physical environment” (PE), “Industry 4.0 technology” (i4.0), “Company culture” (CC), and “Manufacturing methods” (MM) based on a metric, the sociotechnical system (STS) concept. This makes it possible to determine the percentage of participation in Lean and Ergonomics articles by STS category. The main differences can be seen in PE (Lean: 10%; Ergonomics: 24%) and i4.0 (Lean: 29%; Ergonomics: 15%). However, for PW (Lean: 18%; Ergonomics: 21%), CC (Lean: 19%; Ergonomics: 20%), and MM (Lean: 26%; Ergonomics: 20%), there are similarities between Lean and Ergonomics. The OPM user should manage the PW, CC, and MM factors equally with Lean and Ergonomics, as the objective is the same. For PW, CC, and MM measures, a professional separation into Lean/OPM and Ergonomics/Occupational Medicine does not make sense. Concerning i4.0, there is a danger that the human factor in (especially innovation-oriented) OPM will be unjustly neglected and that too much emphasis will be placed on supposedly human-free technology. Keywords Operations management· Production management· Lean ergonomics· Lean management· Human factors engineering· Operational excellence 1 Introduction Operations management and production management (OPM) have evolved from Industry 1.0 to the current phase of Industry 4.0, focusing on the driving forces of change and the market, as well as existing or newly developed methods and technologies (Choi etal. 2022). The risk is that an OPM focused on innovation will neglect existing and equally essential players in a manufacturing enterprise. Disruptive technologies such as artificial intelligence, mobile robotics, 3D printing, digital twins, virtual reality, and others are emerging individually and collectively, providing data for OPM and exploiting other capabilities (Vinitha etal. 2020). A neglected aspect behind the systemand techno-centric methods and technologies of OPM is the user of these tools, the employee, who is directly exposed to the framework of OPM and must be taken into account for strategic decisions of top management (Brunner etal. 2022; Chen etal. 2023). Industry 4.0 methods and technologies act as facilitators of the effects of lean production processes on improving operational performance (Blanco etal. 2023; Ding etal. 2023). The necessary framework for this cause-and-effect relationship is created through holistic OPM (Tortorella etal. 2019). This seems only logical since Lean, in the form of lean production/management, is the gold standard of manufacturing companies in the 21st century, and the specifications and principles of a lean production concept should not only be prepared but also enabled by OPM (Hardcopf etal. 2021). * Stefan Brunner [email protected] 1 Technical University ofMunich, TUM School ofEngineering andDesign, Chair ofErgonomics, Boltzmannstraße 15, D-85747Garching, Munich, Germany 1173Streamlining operations management byclassifying methods andconcepts ofLean andErgonomics… withinasociotechnical framework Ergonomics is the scientific discipline focused on understanding and optimizing human interactions with a (technical) system to provide wellbeing for the human and performance for the system (Dul etal. 2012). Similar to OPM, the discipline developed in response to megatrends and the great industrial revolutions but has always been human-centered. As a result, extreme working hours of up to 16 hours, high accident rates, and complete absence of social security are things of the past (Luczak etal. 2018). However, just as the OPM lacks a connection to the human factor, the significant developments in Ergonomics lack the reference to business science and OPM that would make Ergonomics indispensable for a rational company (Dul and Neumann 2009; Sobhani etal. 2016). According to Chen etal. (2023), holistic OPM must consider the user of all operational methods and technologies, primarily the OPM manager/engineer. However, according to Brunner etal. (2022), more is needed because the end effector in this decision cascade is the production worker, who usually does not participate in OPM decisions but is directly affected by them. This means that there are two sociotechnical levels on which OPM operates (Dworschak and Zaiser 2014); usually, only the level of the production worker is associated with direct productivity and value creation on the one hand, and with classical production ergonomics on the other (Battini etal. 2011; Neumann and Dul 2010). Production ergonomics is often seen as a cost rather than a success factor (Zare etal. 2016). A generalized management approach such as “management by measurement,” on which OPM and the Lean philosophy are based, is not widely used in Ergonomics (Greig etal. 2023), although there are measures and parameters to link production ergonomics to Lean and OPM (Kolus etal. 2018; Yung etal. 2020). As OPM plays a vital role in operational and strategic decisions or prepares them for top management, a comprehensive understanding of lean production and lean management on the one hand and production ergonomics on the other hand is crucial. Therefore, OPM managers and practitioners must understand how Lean as a production and management concept and Ergonomics as a human-centered counterpart work together, alongside each other or against each other. The research question is: In which categories of the sociotechnical system “factory” do Lean and Ergonomics differ? This paper examines the similarities and differences between Lean and Ergonomics using an evaluation system that provides evidence. The paper defines the same standardized evaluation categories for methods and concepts of both Lean and Ergonomics. A literature review then examines which categories of Lean and Ergonomics measures and domains are synergistic or antagonistic. This is important for OPM users because the application of OPM/Lean affects not only productivity and profitability but also an entire sociotechnical system. By „Lean,” we mean the philosophy and discipline derived from lean management, lean production, lean manufacturing, and the Toyota Production System. When it is specified, we write „lean [...].” By „Ergonomics,” we mean the discipline. When it is specified, we write „[...] ergonomics.” 2 Theoretical background First, as depicted in Fig.1, categories of Lean (1) and Ergonomics (2) are selected, filtered, and compiled from research papers and textbooks for later analysis. A metric system including Lean and Ergonomics is selected from the literature (3). Next, the elements of the metric system are further evaluated, and a matrix is created to form a final metric system (4). A scale system is then developed to measure the interdependence between Lean and Ergonomics categories with the metric system (5). After that, the analysis of Lean (7) and Ergonomics (8) with the metric system is carried out using relevant literature (6) and (9). Then, the total and average scores of Lean (10), Ergonomics (11), and the combined characteristics are calculated (12). Lean and Ergonomics are combined in a matrix to compare results and calculate total scores (13). Graphs and charts are drawn for better visualization and analysis (14). Finally, the similarities and differences between Lean and Ergonomics are discussed. 2.1 Categories oflean First, a literature review in Google Scholar and Scopus is conducted with the following search terms: (lean production OR lean manufacturing OR lean implementation OR Toyota Production System) AND (tools OR principles OR methods) to obtain categories of Lean. This literature search was not limited by time frame but by relevance, citations, and timeliness. Timeliness is essential for this literature as a basis for forming the Lean categories in this article because only the current literature covers the latest developments in Lean. Only English-language peer-reviewed sources were included. Articles from Google Scholar were included only if the search terms appeared in the title. Articles from Scopus were included if the search terms appeared in the title or keywords section of the article. Next, all Lean methodologies are compiled and filtered from research reports to create a list of the seven most commonly used tools in the industry based on the articles in this paper, listed below (Top 7 in bold). Table1 shows the compilation of different Lean tools with relevant research papers and textbooks. The top Lean tools used in the industry are Kanban, Kaizen, Pokayoke, 5S (sort, set in order, shine, standardize, sustain), TPM (Total Productive Maintenance), VSM (Value Stream Mapping), and SMED (Single-minute exchange of die) (Dombrowski 2015; Koether and Meier2017), which are also used in this article. 1174 S.Brunner et al. 2.2 Categories ofergonomics In defining the categories of Ergonomics, we have been guided by the International Ergonomics Association (IEA). The IEA divides Ergonomics into “physical,” “cognitive,” and “organizational” Ergonomics. Physical ergonomics includes anatomical, physiological, and biomechanical aspects. It prioritizes the worker's wellbeing, considering environmental factors such as lighting and temperature that affect productivity (Gitahi etal. 2015; McGuire and McLaren 2009). Herzberg’s theory emphasizes the role of the environment in worker performance (Herzberg 2008). Cognitive ergonomics includes mental aspects such as perception and reasoning that affect humansystem interactions (Carayon etal. 2013; IEA 2023). It includes logical reasoning, perception, motor responses, and workplace interactions (IEA 2023). Training is positively correlated with performance (Karimi and Nejad 2018). Organizational ergonomics analyzes and optimizes the macroscopic production system by aligning structures, policies, and processes (IEA 2023). It increases efficiency by considering workers’ activities, abilities, and constraints (Latip etal. 2022). Organizational ergonomics affects employee motivation and performance, critical to business success (Paais and Pattiruhu 2020). 2.3 Literature search based ondefined categories The literature reviewed for the article was limited to the period from 1990 to January 2023. We chose this period because Lean only became widely known in the West with the publication of Womack etal. (1990). Then, it took several years to establish Lean in manufacturing and OPM (Dombrowski 2015). We also wanted to consider the transition from Industry 3.0 to Industry 4.0 (Sakhapov and Absalyamova 2018). In addition, musculoskeletal work-related disorders manifest themselves with a long time lag, which can result in complaints only appearing 20 to 30 years after the introduction of a production or workchanging measure. Production processes that make people sick have not affected the company's profitability, which means that Ergonomics has not been a must-have from a purely economic point of view. With demographic changes and the increasing number of people with reduced performance, this is changing (Anderson-Connolly etal. 2002; Baur 2013). We searched for all possible combinations of [Top 7 items of Lean category] AND [three items of Ergonomics category] in Google Scholar and Scopus (title, abstract, keywords). Only articles and textbooks pertinent to the study’s context and aim are incorporated. The literature review is Fig. 1 Flowchart of the methodology 1175Streamlining operations management byclassifying methods andconcepts ofLean andErgonomics… withinasociotechnical framework not meant to be a thorough and systematic exploration of the literature on OPM, Lean, and Ergonomics. Instead, it aims to summarize their connections, arranged and categorized in new ways to assist OPM users/managers in their decisionmaking and actions. 2.4 The socio‑technical‑system theory The concept of the socio-technical-system (STS) was first introduced by Leavitt (1965), who categorized organizations into people, task structure, and technologies. In 2011, Clegg & Challenger expanded this using six categories: goals, people, infrastructure, technology, culture, and processes, emphasizing their interconnectedness (Clegg and Challenger 2011). This study's metric framework is derived from Clegg and Challenger (2011) and uses five elements adapted to analyze lean production/manufacturing and Ergonomics synergies and contrasts. Table2 shows the adapted elements. The sociotechnical factor “goals” is not included due to industry-specific variations. The remaining five factors are introduced in the following sections. Table 1 Lean tools as categories of Lean used in this paper (Top 7 in bold) a (Andrés-López etal. 2015) b (Adesta etal. 2018) c (Nunes 2018) d (Rewers and Chabowski 2016) e (Sivaraman etal. 2020) f (Pakdil and Leonard 2014) g (Moon etal. 2014) h (Kolberg and Zühlke 2015) i (Nunes 2015) j (Carvalho etal. 2019) k (Leksic etal. 2020) Lean tools a b c d e f g h i j k Total Poka-Yoke/mistake handling x x x x x x x 7 Andon x x 2 Heijunka/level scheduling x x x x x 5 Man-Machine 0 5S x x x x x x x 7 Pull flow/Kanban xxxxxxxxxxx11 VSM xxxx xxx x8 Standardization xxxx xx6 TPM x x x x x x x 7 Visual management x x x x 4 Kaizen xxxx xxxxxx10 JIT (just-in-time) x x x x 4 Jidoka/Automation x x x x 4 SMED x x xxxxx7 Continuous flow x 1 PDCA x 1 Matrix skills x 1 Table 2 Sociotechnical factors from Clegg and Challenger (2011) (adopted for this article) Sociotechnical factors from Clegg and Challenger (2011)Sociotechnical factors used in this article People Production worker Building/ Infrastructure Physical environment Technology Industry 4.0 (i4.0) technology Culture Company culture Procedure/Process Manufacturing methods Goals - 1176 S.Brunner et al. 2.4.1 The production worker For a more detailed analysis, we subdivide the production worker factor according to Sakthi etal. (2019) into four categories: physical, psychosocial, work design, and managerial factors, as shown in Table3. 2.4.2 Company culture The company culture factor used in this paper is taken from the concept from Cameron and Quinn (2011), which is further divided into four categories: hierarchical, market, clan, and adhocracy cultures, as shown in Table4 (Cameron and Quinn 2011). 2.4.3 Physical environment An ideal physical environment of the workplace is where workers’ physical and cognitive abilities can perform at their best and thus achieve the objectives and goals of both workers and the company (Chua etal. 2016). The physical environment factor is further divided into three categories in Table5 (Schlick etal. 2010; Schmauder and Spanner-Ulmer 2022). 2.4.4 Manufacturing process The manufacturing process factor for this paper is divided into labor-intensive and capital-intensive methods. Their descriptions are shown in Table6. 2.4.5 Technology (i4.0) In the technology category from Leavitt (1965), i4.0 technology and tools are adopted as our category in the sociotechnical system. Table7 shows the top i4.0 tools in the industry taken from five research papers. These five articles were used to form the categories, firstly because they are current, which is relevant to technological developments, and secondly because they consider and analyze technology in general in the context of Industry 4.0. 2.5 Hypotheses Now that STS, as the relevant metric, and the categories of Lean and Ergonomics that are grouped in STS via literature are known, the following hypotheses (H) are proposed (see Tab. 8): H1: Industry 4.0 technology is a Lean/OPM category H2: Manufacturing process is a Lean/OPM category H3: Production worker is an Ergonomics category H4: Physical environment is an Ergonomics category H5: Company culture is a Lean/OPM category 2.6 Evaluation matrix Table9 below shows the matrix used to analyze Lean and Ergonomics. The different scales were sorted in ascending Table 3 Production worker factor (Sakthi etal. 2019) Production worker category Subcategory Physical Working posture Weight/force Work intensity Psychosocial Job stress Job satisfaction Work design Job autonomy Job clarity Time pressure Rotation Managerial factor Communication Supervisor/co-worker support Reduction of resources Table 4 Company culture factor Company culture category Description Hierarchical culture The hierarchical culture emphasizes the internal environment of the company. Typical characteristics are welldefined and standardized procedures, roles, and work processes (Reis etal. 2016). Market culture Market culture focuses on controlling the external environment, in which workers strive to achieve goals to meet customers’ demands (Cameron and Quinn 2011). Clan culture Clan culture focuses on the internal environment and highlights the human factor, whereby workers are valued and appreciated (Cameron and Quinn 2011). Adhocracy culture Adhocracy culture focuses on the external environment and flexibility, whereby workers are encouraged to explore and innovate products (Cameron and Quinn 2011). 1177Streamlining operations management byclassifying methods andconcepts ofLean andErgonomics… withinasociotechnical framework and descending order using Microsoft Excel. This way, it is possible to visualize the categories with the highest and lowest degrees. This analysis employs a binary scale, wherein “X” denotes a positive interdependence, while “blank” indicates a negative or no interdependence. “Negative or no interdependence” was defined as: negative interdependence, no interdependence, and no information. Category headings for Table 5 Physical environment factor (for details, see Luczak etal. 2018; Schmauder and Spanner-Ulmer 2022) Physical environment category Description Temperature The workplace temperature should be a minimum of 13°C for production workers to work productively. Lighting The workplace lighting must be bright enough to prevent eyestrain, stress, and accidents and improve productivity. Noise Noise is defined as all the sound in the workplace, either wanted or unwanted. It is one of the most common Occupational Health and Safety (OHS) hazards and is found in different environments (Trebuna etal. 2017). Table 6 Manufacturing process factor Manufacturing process categories Description Labor-intensive Manufacturing process has more human labor than production machinery (Kenton 2003). Capital-intensive Manufacturing process relies on machinery rather than labor to produce goods and services (Frankenfield 2003). Table 7 Analysis of the i4.0 technology tools a (Mayr etal. 2018) b (Jiang etal. 2021) c (Mayr etal. 2017) d (Vinodh and Wankhede 2021) e (Chae and Olson 2022) I4.0 technology tools a b c d e Total Additive manufacturing (AM) x x x x x 5 Machine learning (ML) x x x x x 5 Plug and play x 1 Human-Computer Interaction (HCI) x x x x 4 Virtual/Augmented reality (VR/AR) x x x x x 5 Digital twin x x x x 4 Big data and analytics x x x x x 5 Cloud computing x x x x x 5 Blockchain x x 2 Table 8 Hypotheses of the category of sociotechnical factors Hypothesis Lean/OPM I4.0 technology Manufacturing process Company culture Ergonomics Production worker Physical environment 1178 S.Brunner et al. Lean or Ergonomics in Table9 are denoted by letters “a,” “b,” and so on and are marked in blue. For Lean, these categories may include Poka-Yoke, Kaizen, and so on, while for Ergonomics, they include physical, cognitive, and organizational Ergonomics. Table10 shows the formulas to compute the values required for further evaluation. The association between Lean and Ergonomics with the sociotechnical factor is evaluated using the binary scale in the blue-shaded cells. Then, the cumulative score of each subcategory of the Lean and Ergonomics evaluations is ascertained in the red-shaded cells. The analysis of (i) is done by calculating (ii), (iii), and (iv) (Table10). (ii) The average Lean or Ergonomics score of a subcategory of sociotechnical factors shows the correlation of each subcategory of sociotechnical factors with Lean or Ergonomics. The scores in the green cells are calculated using (i) the sum of all Lean or Ergonomics categories scores in each sociotechnical subcategory divided by the percentage of the number of Lean or Ergonomics categories. (iii) The weighted average Lean or Ergonomics score of each sociotechnical factor subcategory is the same as (ii) with additional weighting. (iii) The scores in the purple cells are calculated by taking the average Lean or Ergonomics scores in (ii) and dividing by the number of Table 9 Evaluation matrix of Lean and Ergonomics Table 10 Mathematical formulas used in the analysis Variable Formula (with sample entries) i Total score of each sociotechnical subcategory Total score of each sociotechnical subcategory = ∑ SMED or organizational ergonomics n=Poka−Yoke or physical ergonomics Lean or Ergonomics in binary (n ) ii Average Lean or Ergonomics score of a subcategory of sociotechnical factor The average score of each subcategory of the sociotechnical factor = ∑ SMED or organizational ergonomics n=Poka−Yoke or physical ergonomics score of each subcategory (n) # of Lean or Ergonomics categories ∗100 % iii Weighted average Lean or Ergonomics score of each subcategory of sociotechnical factor Weighted average score =Average Lean or Ergonomics score of each subcategory # of subcategories of a sociotechnical factor iv Score of sociotechnical factor (%) Score of sociotechnical factor = ∑ SMED or organizational ergonomics n=Poka−Yoke or physical ergonomics Weighted average score of subcategory 1179Streamlining operations management byclassifying methods andconcepts ofLean andErgonomics… withinasociotechnical framework subcategories of a sociotechnical factor. The Lean or Ergonomics scores of the sociotechnical factors (iv) determine the correlation between Lean or Ergonomics and the sociotechnical metrics and are calculated using the sum of (iv). 3 Results Table11 shows the results of Lean and Ergonomics scores on the sociotechnical metrics. Average and weighted Lean and Ergonomics scores are computed using the formula in Table10 (see appendix for single evaluation matrix). Technology (i4.0) and manufacturing process, with 71% and 64%, respectively, are the highest-scoring sociotechnical factors for Lean categories (blue bars) (Fig.2). The third highest Lean score is the company culture factor, which has an average Lean score of 46%. Figure3 also shows the evaluation of Ergonomics with the sociotechnical metrics (orange bars); the physical environment category has the highest Ergonomics score, which is 100%. All three categories of Ergonomics are positively correlated with the physical environment factors such as temperature, sound, and noise. The second-highest Ergonomics score is in the category of production workers, with a score of 86%. At first glance, cognitive Ergonomics is not correlated with the physical characteristics of production workers: posture, weight or force, and porosity. Two categories that score 83% are company culture and manufacturing process factors, considered both Lean and Ergonomics. Hierarchy and clan cultures are strongly associated with Ergonomics, while adhocracy and market cultures are less correlated. Despite being more specific than categories Table 11 Summary of Lean and Ergonomics score using the sociotechnical metrics Sociotechnical factor Average Lean score Average Ergonomics score Weighted Lean score Weighted Ergonomics score Physical environment 24% 100% 9% 24% Production worker 44% 86% 17% 21% Company culture 46% 83% 21% 20% Manufacturing process 64% 83% 25% 20% Technology (i4.0) 71% 67% 28% 15% Total / / 100% 100% 24% 44%46% 64% 71% 100% 86% 83%83% 67% 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Physical environment Production worker Company cultureManufacturing process Technology (i4.0) Score (%) Socio-technicalfactor Lean score Ergonomics score Fig. 2 Bar chart of the comparison of Lean and Ergonomics using the sociotechnical metrics 1186 S.Brunner et al. Table 17 Lean score of technology (i4.0) factor a (Pancha 2022) b (Tortorella etal. 2021) c (Feldmann and Gorj 2017) d (Br unner 2011) e (Mayr etal. 2018) f (Ciano etal. 2021) g (My 2021) h (Jardine etal. 2006) i (Lucke etal. 2017) j (Thakur etal. 2020) k (Rammelmeier etal. 2012) l (Pötters etal. 2017) m (Palmarini etal. 2018) n (Benbelkacem etal. 2011) o (Cudney etal. 2011) p (Tothong etal. 2020) q (Saltz and Suthrland 2019) r (Lucke etal. 2017) s (Kieviet 2016) t (Varian 2014) u (Wijaya etal. 2020) v (Reyes etal. 2023) w (Neges etal. 2017) x (Kolberg and Zühlke 2015) y (El Abbadi etal. 2011) z (Thakur and Panghal 2021) aa (Kanta Patra etal. 2005) bb (Cavadini and Pedrazzoli 2018) cc (Zhihan etal. 2023) dd (Deng etal. 2022) ee (Trebuna etal. 2019) ff (Lu etal. 2021) gg (Barni etal. 2020) hh (Umeda etal. 2020) ii (Guo etal. 2021) I4.0 technology category Poka-Yoke 5S Kanban VSM TPM Kaizen SMED AM XaXbXc,e ML Xd,e,f Xf,v XgXh,i,b XjXf VR/AR XkXl,o Xm,n XoXp,o Big data & analytics XeXqXrXs,b Xf,t Cloud computing Xe,u XvXb HCI/HMI XeXw,x XyXeXz,aa Xbb Digital twin Xe,cc Xdd XxXee,ff Xgg Xf,hh Xii 1187Streamlining operations management byclassifying methods andconcepts ofLean andErgonomics… withinasociotechnical framework Appendix2: Ergonomics evaluation See Tables18, 19, 20, 21, and 22. Table 18 Ergonomics score of production worker factor a (Otto and Battaïa 2017) b (Jarebrant etal. 2015) c (Vincent etal. 2015) d (Koukoulaki 2014) e (Sakthi etal. 2019) f (da Costa and Vieira 2010) g (van Rijn etal. 2010) h (Jonker etal. 2011) i (Jahncke etal. 2011) j (Lagomarsino etal. 2022) k (Bryson etal. 2017) l (Shobe 2018) m (Olla 2012) n (Bouville and Alis 2014) o (Rodríguez etal. 2016) p (Chung-Yan 2010) q (Hasle etal. 2012) r (Edwards 2014) s (Falck etal. 2014) t (Sprigg and Jackson 2006) u (Ehrensberger-Dow and O'Brien 2015) v (Bednárová-Gibová 2021) w (Berlin and Adams 2017) Production worker category Subcategory Physical ergonomics Cognitive ergonomics Organizational ergonomics Physical Working posture Xa,b,c,d Xm Physical Weight/force Xa,e,f,g Xm Physical Physical porosity Xa,b,h Xm,b Psychosocial Job stress XdXi,j Xm Psychosocial Job satisfaction XdXk,l Xm,u,n,o Work design Job autonomy XdXpXq Work design Job clarity XrXsXt Work design Time pressure XdXuXv,d Work design Rotation XsXn Managerial factor Communication XdXwXw,v,m Managerial factor Supervisor support XdXwXu Managerial factor Reduction of resources XwXu 1188 S.Brunner et al. Table 19 Ergonomics score of company culture factor a (Paz etal. 2020) b (Hendrick and Kleiner 2005) c (Schutz etal. 2007) d (Zahari and Shurbagi 2012) e (Dubkēvičs and Barbars 2010) f (Olynick and Li 2020) g (Goodman etal. 2001) h (Olla 2012) Company culture category Physical ergonomics Cognitive ergonomics Organizational ergonomics Hierarchy culture XaXd,f Xb,c,e Market culture XdXe Clan culture XaXd,f,g Xh Adhocracy culture XaXd,f Table 20 Ergonomics score of physical environment factor a (Olla 2012) b (Berlin and Adams 2017) c (Jaffar etal. 2011) d (Thaneswer 2013) e (Vimalanathan etal. 2017) f (Hendrick and Kleiner 2005) g (Taghipour 2015) h (Vischer 2007) i (Juslén etal. 2007) j (Jahncke etal. 2011) k (Couffe and Michael 2017) l (Jafari etal. 2019) m (Sundstrom etal. 1994) n (Stokols and Scharf 1990) o (Hedge 1986) p (Oldham 1988) Physical environment category Physical ergonomics Cognitive ergonomics Organizational ergonomics Temperature Xa,b,c Xd,e Xf,g Lightning Xa,b Xh,d,i Xf,g Noise Xa,b Xj,k,l,m Xf,g,n,o Table 21 Ergonomics score of manufacturing process factor a (Akca and Küçükoğlu 2020) b (Latip etal. 2022) c (Larson etal. 2015) d (Peruzzini and Pellicciari 2017) e (Ciccarelli etal. 2022) f (Morsy etal. 2016) g (Karwowski and Marras 1998) Manufacturing process category Physical ergonomics Cognitive ergonomics Organizational ergonomics Labor-intensive XaXb,c Capital-intensive Xd,e Xf,g,e Xg Table 22 Ergonomics score of technology (i4.0) factor a (González etal. 2018) b (Stoklasek etal. 2016) c (Da Silva etal. 2020) d (Hummel etal. 2015) e (Lee etal. 2021) f (D’Orazio etal. 2020) g (Lazarova-Molnar etal. 2017) h (Longo etal. 2017) i (Richert etal. 2016) j (Horváth and Erdős 2017) k (Scheuermann etal. 2016) l (Chiabert and Aliev 2020) m (Kadir etal. 2019) n (Stern and Becker 2017) o (Pacaux-Lemoine etal. 2017) p (Tatić and Tešić 2017) q (Ahmed 2019) r (Panagou etal. 2021) s (Segura etal. 2020) t (Hou etal. 2021) u (Montini etal. 2021) v (Du etal. 2020) w (Fu etal. 2016) x (Fatorachian and Kazemi 2018) I4.0 technology category Physical ergonomics Cognitive ergonomics Organizational ergonomics AM Xa,b Xc ML Xd,e Xf,g Xh VR/AR Xi,j,k XlXm,n,o,h Big data & analytics Xp,q Xr,s Cloud computing XtXu,v,w HCI/HMI Xx Digital twin Xh,o 1189Streamlining operations management byclassifying methods andconcepts ofLean andErgonomics… withinasociotechnical framework Funding Open Access funding enabled and organized by Projekt DEAL. No funding was received for conducting this study. Data Availability Statement for material and data availability does not apply as all data is freely available. Declarations Ethical approval An ethics vote was not required for this work. Conflict of interest The authors declare that they have no conflict of interest and no competing interest. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. 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