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."
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."