Does Inappropriate Quality Control Demotivate Workers

The construction industry requires quality control and regulation of its contingent,unpredictable environment. However, taking too much control from workers candisempower and demotivate. In the 1970s Deci and Ryan developed selfdeterminationtheory which states that in order to be intrinsically motivated, threecomponents are necessary - competence, autonomy and relatedness. This study aimsto examine the way in which the three ‘nutriments’ for intrinsic motivation may beundermined by heavy-handed quality control. A critical literature review analysesconstruction, psychological and management research regarding the control andmotivation of workers, using self-determination theory as a framework. Initialfindings show that quality management systems do not always work as designed.Workers perceive that unnecessary, wasteful and tedious counter checking of theirwork implies that they are not fully trusted by management to work without oversight.Control of workers and pressure for continual improvement may lead to resistanceand deception. Controlling mechanisms can break the link between performance andsatisfaction, reducing motivation and paradoxically reducing the likelihood of thequality they intend to promote. This study will lead to a greater understanding ofcontrol and motivation, facilitating further research into improvements in theapplication of quality control to maintain employee motivation.

Process Selection Using Variation and Cost Relations

Variations are inherent in all manufacturing processes and can significantly affect the quality of a final assembly, particularly in multistage assembly systems. Existing research in variation management has primarily focused on incorporating GD&T factors into variation propagation models in order to predict product quality and allocate tolerances. However, process induced variation, which has a key influence on process planning, has not been fully studied. Furthermore, the link between variation and cost has not been well established, in particular the effect that assembly process selection has on the final quality and cost of a product. To overcome these barriers, this paper proposes a novel method utilizing process capabilities to establish the relationship between variation and cost. The methodology is discussed using a real industrial case study. The benefits include determining the optimum configuration of an assembly system and facilitating rapid introduction of novel assembly techniques to achieve a competitive edge.

New Method Based on the UNIFAC–VISCO Model for the Estimation of Ionic Liquids Viscosity Using the Experimental Data Recommended by Mathematical Gnostics

The viscosity of ionic liquids (ILs) has been modeled as a function of temperature and at atmospheric pressure using a new method based on the UNIFAC–VISCO method. This model extends the calculations previously reported by our group (see Zhao et al. J. Chem. Eng. Data 2016, 61, 2160–2169) which used 154 experimental viscosity data points of 25 ionic liquids for regression of a set of binary interaction parameters and ion Vogel–Fulcher–Tammann (VFT) parameters. Discrepancies in the experimental data of the same IL affect the quality of the correlation and thus the development of the predictive method. In this work, mathematical gnostics was used to analyze the experimental data from different sources and recommend one set of reliable data for each IL. These recommended data (totally 819 data points) for 70 ILs were correlated using this model to obtain an extended set of binary interaction parameters and ion VFT parameters, with a regression accuracy of 1.4%. In addition, 966 experimental viscosity data points for 11 binary mixtures of ILs were collected from literature to establish this model. All the binary data consist of 128 training data points used for the optimization of binary interaction parameters and 838 test data points used for the comparison of the pure evaluated values. The relative average absolute deviation (RAAD) for training and test is 2.9% and 3.9%, respectively.