Industry 4.0 as the Cybernetisation of Production

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* Article: From the smart factory to the self-organisation of capital: ‘Industrie 4.0’ as the cybernetisation of production. Simon Schaupp and Ramon Diab. Ephemera, volume 20(4), 2020.

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Contextual Quote

"there are visions of the self-organization of industrial capital reaching a point where labour-power is replaced entirely with machine-power in fully automated smart factories. This would require either retrofitting, or replacing entirely, all pre-existing machines with cyberphysical control systems (Roblek et al., 2016: 4) as well as digitalising and integrating cyberphysical control over the flow of all raw materials, production processes and produced commodities. Such a fully automated production process would involve all raw materials wirelessly transmitting instructions to surrounding machines that automatically and flexibly produce each commodity on demand and to specification (Siemens, 2013). We suggest that if the design and implementation of fully autonomous smart factories becomes ubiquitous to the point of raising the organic composition of capital, this process would represent an advance of capital’s real subsumption of the labour process toward a third and final stage of capital’s autonomisation from labour-power, the realisation of which could theoretically lead to the dissolution of the labour-capital relation."

- Simon Schaupp and Ramon Diab pdf


"Governments and private sectors have collaborated on national initiatives that will introduce ‘cyberphysical systems’ and the ‘industrial internet of things’ to the sphere of production in a new wave of capitalist development currently referred to in Germany as ‘Industrie 4.0’. We refer to the historical and technical development of the means of control within the capitalist mode of production that began with scientific management, management cybernetics, digital process control, and now Industrie 4.0, as the cybernetisation of production. This article analyses the German context of Industrie 4.0 as a new regime of production. Data drawn from a series of semi-structured interviews with managers and engineers of Industrie 4.0 companies reveal current developments and future visions for the digital transformation of German industry. Based on these data and some theoretical considerations, we argue that Industrie 4.0 is designed to automate the self-organisation of industrial capital in ‘smart factories’. This will shift the personal control of middle management toward the more direct and immediate cybernetic control of market forces over the production process. The article concludes that as direct labour and managerial labour is replicated, extended and/or entirely replaced with autonomous machines, the cybernetisation of production is advancing capital’s real subsumption of the labour process toward capital’s autonomisation from labour-power, which is creating new autonomous forms of production."


Simon Schaupp and Ramon Diab:

"This article begins with a historical review of the scientific, technical and management paradigms that have developed the human and non-human means of feedback over the labour process. We refer to this as the historical process of the cybernetisation of production, which creates new forms of cybernetic work and leads toward full automation of the labour process. As cyberphysical systems are rooted in the control logic of cybernetics, we therefore suggest that Industrie 4.0 is the technical realisation of capital’s self-organisation, extending from the shop floor to the top floor of ‘smart factories’.

The article then analyses empirical data from an ongoing research project to illustrate the historical continuity of Industrie 4.0 as part of the contemporary process of the cybernetisation of production. The empirical data stem from a series of 20 semi-structured ‘comprehensive interviews’ (Kaufmann, 2015). Interviewees were managers and engineers of companies based in the German high-tech industry areas of Bavaria and Baden Württemberg who consider themselves to be part of Industrie 4.0. The cases were selected to generate an overview of the vision pursued by engineers and managers of industrial organisations as exemplars of the digital transformations of Industrie 4.0. The data were analysed with the coding software dedoose according to the standards of qualitative content analysis. The code system followed the theoretical research question but was, in its concrete form, derived inductively from the material (Kuckartz, 2016). Drawing on the empirical data, we argue that the introduction of the industrial internet of things and cyberphysical systems to the sphere of production will advance industrial capital’s self-organisation of the production process. Industrie 4.0 therefore could advance what Marx referred to as capital’s real subsumption of the labour process toward a third and final stage that we refer to as capital’s autonomisation from labour-power, which we suggest could lead to a new autonomous mode of production."



The Cybernetic Production Regime

Simon Schaupp and Ramon Diab:

"The entanglement of state-driven ideology and the technological development of industry is best grasped by Burawoy’s (1985) notion of a production regime. According to Burawoy, a production regime refers to the intersection of state politics and the politics of production that regulates industry. By extension, we argue that, through the implementation of networked digital technologies, Industrie 4.0 is part of the historical process of the cybernetisation of production that represents the tendency of industrial capital to become increasingly autonomous from the labour-capital relation. This leads toward a cybernetic regime (Schaupp, 2017a). The following analysis develops this argument by discussing how middle managers became capital’s early means of delivering feedback to the labour process, which would eventually be replicated, extended and/or replaced with automation technologies as the means of cybernetic control over the labour process."


The History of the Cybernetisation of Production

Simon Schaupp and Ramon Diab:

"The introduction of scientific management to the assembly line in the early twentieth century focused initially on the production of a greater mass of products in the same or smaller amount of time by calculating the number of products produced within the labour process. Scientific management physically restricted options for deviating practices on the side of the workers and was therefore often quoted as the prime example for technical control (Edwards, 1979). At about the same time, large industrial companies began to introduce differentiated rules and procedures, fostering a top-down hierarchical order that was described as bureaucratic control (ibid.). Both technical and bureaucratic control became the basis for scientific management, which developed in the Fordist era as a result of the division of manual labour of production from the cognitive labour of management and planning (Braverman, 1974). The replication of this division of labour in turn further divided social development of the technical aspects of manual and cognitive labour.

Grids, graphs, and other informational tools for measuring the labour process provided management the means of objectifying, and thus representing, various aspects of the labour process in data. Scientific management included measurements of the labour process such as Taylor’s ‘time studies’. These measures would become coupled with the motion studies of Gilbreth when managers calculated the physical motion of the labour process in relation to the number of products produced in a given amount of time for the purpose of identifying inefficient activity (Gilbreth and Kent, 1921; Taylor, 1913). These forms of analyses were used for the systematic measurement of productivity in the labour process in order to physically alter it for the purpose of increasing productivity, and therefore, total output. The forms of managerial action taken as a result of these measures were therefore an early form of data-driven feedback. Hence, scientific management’s systematic and detailed collection of data from the labour process foreshadowed the logic of cybernetic control in industrial production, but in a form more heavily reliant on human managers. Central hierarchical order, however, was still personified at its core by the figure of the manager, inspiring Edwards (1979: 132) to write about a ‘managerial revolution’. In this respect, industrial capital developed its own human means of control over the labour process through the division, reorganisation, and thus, development of the productive forces of labour in the historical stage of capital’s real subsumption of the labour process. This meant that managers functioned as capital’s means of control over the direct labour process through the open-loop of managerial feedback. Thus, we suggest that the development of managerial labour is capital’s historical development of the means of enforcing the technical requirements of valorisation within the production process.

As Noble (2011) noted, the history of the ‘automatic factory’ began with the development of the process industries in the early twentieth century. These were developed on the principles of process control that were objectified in the development of industrial automation technologies that replicated, extended and/or replaced the labour-power of the direct production process.

As Noble (2011: 59) described it, ‘all continuous process production demanded unprecedented devices-sensors and effectors (actuators) for carefully monitoring and adjusting direct production operations too complex for complete human oversight and manual control’. However, early computerisation meant that process manufacturing still relied on the decisions of human operators to monitor and respond to the production process based on the information produced by computers, which is understood as an open-loop form of feedback. Hence, early process control was neither about physically restricting options – as in technical control – nor about bureaucratic top-down order. Rather, its primary goal was the development of computer monitoring combined with human control in the direct production process. With the development of closed-loop automation in the process industries, automation technologies that were produced and used as the means of control of the direct production process were developed to replicate, extend and/or replace the labour-power of managerial feedback. The principles of control were later formalised with the development of cybernetics, an interdisciplinary science that was shaped by neurophysiology, information theory, statistical mechanics, psychiatry, physics, biology, anthropology and other sub-disciplines in the natural and social sciences (Kline, 2015). Cybernetics was conceived and promoted during the well publicised Macy conferences in the post-wartime era of the late 1940s and 1950s by natural and social scientists such as Norbert Wiener, Claude Shannon, Ross Ashby, Margaret Mead and Gregory Bateson who had aspirations to develop it as a universal science of control and communication (Wiener, 1948). Early cybernetic theory was initially derived from observations on the self-organisation of biological systems that ‘automatically’ adapt to changes in the environment instead of first making a cognitive plan or hierarchical instruction. Its epistemology relied on models, analogies and other abstract representations of complex systems for the purpose of interdisciplinary comparison, including, for example, modelling the human nervous system as an electronic machine and vice versa.

At its core, cybernetics used prediction and filtering to combine communications and control engineering (Kline, 2015: 22). Feedback loops were designed to bring a given system to a state that cyberneticists call homeostasis. For this, at least two entities influence each other through mutual feedback until they reach a state of equilibrium. Homeostasis, however, was not conceptualised as a static optimum. Rather, homeostasis was considered a dynamic process of optimisation through adaptation, referred to as the Viable System Model (Beer, 1959). With the development of management cybernetics, industrial managers adapted cybernetic principles to the design and management of human communication in organisations, while engineers objectified the general principles of cybernetic control in the production of machines designed to replicate, extend and/or replace both the productive forces of labour and managerial feedback in industrial production."


Integration of the industrial internet of Things with industrial cyberphysical systems

Simon Schaupp and Ramon Diab:

"In contrast to the cyberphysical paradigm, the internet of things (IoT) paradigm originated in the computer science community. As it has been well documented, the Internet first began as a US military project with the development of the ARPANET nodes in the late 1960s and early 1970s (Levine, 2018). While these nodes were later expanded to the university system, and eventually, to the commercial sector, it was not until 1999 that the phrase ‘the internet of things’ was first used to refer to the use of computers for producing knowledge about ‘things’ and the efficiencies this knowledge could bring to industry. Early applications of the ‘industrial internet of things’ (IIoT) were used to organise and control the flow of data and people with technologies such as product data management and product lifecycle management (Jeschke et al., 2017: 5). Therefore, ICPS refers to information technologies that are applied to the direct production process and the IIoT refers to information technologies that are applied to overall production planning and management and that may integrate with ICPS technologies. On this point, it has been suggested that the objective of the IIoT is to fully digitise and network all ‘things’ and processes in factories for the purpose of creating digital or ‘smart factories’ (Krumeich, 2016). Wang et al. conceptualize smart factories as a dual closed-loop system in which ‘one loop consists of physical resources connected to a ‘cloud’, while the other loop consists of supervisory control terminals and cloud’ (Wang et al., 2016: 159). This dual closed-loop system connects smart objects on the shop floor with control technologies at the management level which are in turn connected to global smart factory monitoring and control systems. With respect to the intended purpose of designing and implementing higher-level production planning systems in smart factories, the interviewees have stated that their systems will eliminate the influence of human managers in order to make production ‘organise itself’.

One developer of a cyberphysical system – who aims to connect different levels of industrial control systems from the point of enterprise resource planning (ERP) to the point of control over individual operations – explained that the efficiency gains his system provides are specifically due to the replacement of human planning and decision making with automated data analytics:

- You don’t have any management -influence. Especially with the keyword ‘lot size one’, it is exactly about this planning organising itself, that you always have enough material, that the material is there in time, that the machines are always running. Management decisions only occur if I either have a scarcity of resources or in case of some exceptional situations. (our emphasis)

The claim here is that it is precisely the replacement of human production planning with automated data analytics that increases production efficiency. The IIoT may also reduce production time by predicting machine maintenance and by tailoring commodity production more precisely to the requirements of both industrial and consumer demand, which suggests that Industrie 4.0 will automate several aspects of the lean manufacturing paradigm (Sanders et al., 2016)."