Operator agency in process intervention: tampering versus application of tacit knowledge

Abstract

Statistical process control (SPC) theory takes a negative view of adjustment of process settings, which is termed tampering. In contrast, quality and lean programmes actively encourage operators to acts of intervention and personal agency in the improvement of production outcomes. This creates a conflict that requires operator judgement: How does one differentiate between unnecessary tampering and needful intervention? Also, difficult is that operators apply tacit knowledge to such judgements. There is a need to determine where in a given production process the operators are applying tacit knowledge, and whether this is hindering or aiding quality outcomes. The work involved the conjoint application of systems engineering, statistics, and knowledge management principles, in the context of a case study. Systems engineering was used to create a functional model of a real plant. Actual plant data were analysed with the statistical methods of ANOVA, feature selection, and link analysis. This identified the variables to which the output quality was most sensitive. These key variables were mapped back to the functional model. Fieldwork was then directed to those areas to prospect for operator judgement activities. A natural conversational approach was used to determine where and how operators were applying judgement. This contrasts to the interrogative approach of conventional knowledge management. Data are presented for a case study of a meat rendering plant. The results identify specific areas where operators' tacit knowledge and mental model contribute to quality outcomes and untangles the motivations behind their agency. Also evident is how novice and expert operators apply their knowledge differently. Novices were focussed on meeting throughput objectives, and their incomplete understanding of the plant characteristics led them to inadvertently sacrifice quality in the pursuit of productivity in certain situations. Operators' responses to the plant are affected by their individual mental models of the plant, which differ between operators and have variable validity. Their behaviour is also affected by differing interpretations of how their personal agency should be applied to the achievement of production objectives. The methodology developed here is an integration of systems engineering, statistical analysis, and knowledge management. It shows how to determine where in a given production process the operator intervention is occurring, how it affects quality outcomes, and what tacit knowledge operators are using. It thereby assists the continuous quality improvement processes in a different way to SPC. A second contribution is the provision of a novel methodology for knowledge management, one that circumvents the usual codification barriers to knowledge management. InterventionAlso, although the idealised funnel experiment is highly relevant to the parts manufacturing industries, it is 404 J Ind Eng Int (2015) 11:403-425 J Ind Eng Int (2015) 11:403-425 405

Deming’s tampering revisited: definition and future research agenda

“…4.3.1 Tampering and knowledge about variation. In the literature, the view of tampering is strongly associated with responses to variation in manufacturing processes such as overreactions to small shifts in performance (common cause variation) through, for example, unnecessary adjustment to machine settings (Van Gestel et al, 2015;Georgantzas, 2018). Similar examples occur in health care in terms of making unnecessary adjustments to medicine dosage whenever there is a change in a parameter (Schiff, 1994;Fisher and Welch, 1999) and unnecessary changes in operative routines because of sporadic adverse outcomes of treatment (Morton et al, 2010).…”

“…Despite that they are praised by experts for their wide application (MacCarthy and Wasusri, 2002), effectiveness and simplicity to understand and adopt, their use is still limited (Grigg and Walls, 2007; Halim Lim et al , 2017; Lundkvist et al , 2020) especially in the service sector (Lundkvist et al , 2020). Evidence points to multiple challenges and complications that arise when applying control charts both inside and outside of conventional applications such as need of statistical knowledge, demands on underlying process conditions and variable selection (MacCarthy and Wasusri, 2002; Van Gestel et al , 2015). Moreover, the high level of variation in many service processes makes it difficult to isolate individual quality characteristics to measure and follow-up in a meaningful way (Ojasalo, 2019).…”

“…Many scholars have conceptually repeated Deming’s view of tampering and have provided anecdotal examples (Latzko, 1989; Joiner and Gaudard, 1990; Davis, 2000). Articles in the review presenting practical implications of tampering focus on manufacturing (Van Gestel et al , 2015; Georgantzas, 2018; Davis, 2000), business and economics (Roberts, 1990), education (Coleman, 1999), forest management (Bednar and Shainsky, 1996), health care (Schiff, 1994; Fisher and Welch, 1999; Deyo, 2002; Morton et al , 2010; Smeds and Poksinska, 2019), public sector (Gerst, 1995) and service sector (Gal et al , 2021). More specifically, the articles link tampering to the fields of health-care policy (Gerst, 1995), knowledge management (Van Gestel et al , 2015), product development (Blumstein, 1995), decision-making (Latzko, 1989; Roberts, 1990), system dynamics (Georgantzas, 2018) and quality assessment programmes (Davis, 2000).…”

“…Despite dedicated efforts from organisations to make process improvements, scholars continuously report about failed initiatives (McLean et al , 2017; Antony and Gupta, 2019), actions not resulting in improvements and, in worst case, actions having negative impact on a process (Van Gestel et al , 2015; Georgantzas, 2018). One possible reason for these undesirable results is difficulties in identifying the major root cause problems (Sunder and Prashar, 2020).…”

Lean Manual Assembly 4.0: A Systematic Review

“…Another tension exists related to judgment-based operator adjustments to processes, which could be considered as tampering from the Statistical Process Control (SPC) point of view. Operator adjustment is not always bad, but a necessity in real production plants, and there are methods to determine whether the operator judgment was appropriate or not [217].…”