ABSTRACTThis paper investigated the influence of subcontracting on innovation and its impact on the performance of small and medium enterprises (SMEs) in Onitsha, Nigeria. The paper adopted a number of methods comprising of field observations, reference to relevant literature, and a questionnaire survey of 113 SMEs. Regression, mean and standard deviation were used to analyse the data. In line with the literature, this paper identified seven (7) dimensions of subcontracting assistance from large scale industries to small business firms. The paper found that subcontracting relationship between large scale industries and SMEs is inclined to production and product-related cooperation where the contractors are concerned with meeting fluctuation in demand and shortening long delivery times. This paper concluded by suggesting that subcontracting relationship between SMEs and large scale industries should not be restricted to production, purchase, finance and marketing assistance. It should also be extended to human resource development and organisational-know-how.

ABSTRACTIn Lean Production training and education, simulators are often used. These can take the form of for instance desktop games, computer simulations, or full-scale simulators. Many training participants perceive models for experiential learning and for continuous improvement processes as complex and abstract. Based on experiences from training sessions in a full-scale simulator Karlstad Lean Factory®, a unified model for learning and improvement work is presented. This model stimulates training transfer and is perceived as intuitive. It also shows instructional scaffolding as a learning method. Suggestions for future work include investigating synergy with Smart Manufacturing and the use of Lean Production simulators for innovative product realisation.

ABSTRACTThough Bangladesh is one of the largest garments manufacturing country in the world and there happened revolutionary changes more than four decades ago, they couldn’t achieve sustainable platform yet. The failure to achieve up to the requirement level for the competitive capabilities/manufacturing metrics is the common phenomenon for the manufacturers. Even there is an alarming issue that the manufacturers yet don’t know how they are affected by these failures and also can’t measure how much they are statistically fit. By being motivated from manufacturer’s failure, we worked on a manufacturing unit of a garments industry where we aggregated manufacturing metrics and determined how the manufacturers are affected by the failure of these metrics. This research work will conclude by proposing few models with their mathematical and graphical explanation. By using these models, the manufacturers will be able to determine their strategic fitness, security level, and associated loss/penalty.

ABSTRACTLean Management (LM) is one of the most widely used business strategies for the last three decades. Industry 4.0 shows all the promise of the fourth industrial revolution using automation technologies like cyber-physical systems, internet of things and cloud computing. The purpose of this paper is to propose an integration model of Industry 4.0 and LM. A summary literature review of Industry 4.0 and LM is carried out to construct a theoretical model of integration. The previous literature is used to develop and propose an integration model of Industry 4.0 and LM. The horizontal, vertical and end-to-end engineering integration model are integrated with LM methodology. Testable research propositions are proposed between Industry 4.0 and LM. The model proposed is novel and it raises the important issue of integration of LM with Industry 4.0. This is the first paper which proposes the integration framework of LM with Industry 4.0.

ABSTRACTContinuous flow is the guiding star for lean thinking and considered the ideal state for value streams. Despite this objective, it is seldom possible to obtain a state of continuous flow in a wider context. Decision makers face dynamic environments, and variable internal preconditions require a flow-thinking approach that provides support in response to these challenges. In the present study, the underlying logic of flow thinking is first identified as the key management layer, and thereafter the effectiveness of flow is targeted. The vision of continuous flow is challenged by different exogenous requirements that result in flow discontinuities. Flow thinking is then used to identify 10 decision categories based on these discontinuities, each related to a type of decoupling point and classified as time-based (exogenous) or conversion-based (endogenous). The flow-thinking approach is finally applied in three different contexts: a time-phased product structure, a modularized approach for planning and control, and a mixed-model value stream.

Manufacturing companies need to continuously innovate in order to remain competitive. Fostering a successful innovative environment should reflect positively on manufacturing performance, with a premise that companies seek to attain appropriate level of readiness when deploying their innovation. This paper presents an approach to assessing innovation deployment readiness in manufacturing. Deployment is conceptualised as a sequential decision process that involves a deployment plan to be executed sequentially in an uncertain environment. The deployment plan is assessed using simulation to account for risks and uncertainties that may characterise the deployment activities in the target environment and the capabilities put forward in the plan for handling the risks and uncertainties. The approach is illustrated using a simulated manufacturing job shop scenario and the results show that deployment readiness can vary over time. Deployment readiness can be improved by identifying the states in which readiness is weak and taking appropriate actions.

Companies may receive forecast upsides that can undermine their ability to support customer demand on time. Therefore, it is critical to include forecast upsides when performing comparative analysis of inventory classification models. This study focuses on this subject. The study includes statistical methods and sensitivity analysis to determine the performance of which MCIC model is statistically significant with respect to inventory and customer orders fill rate. Results show that the PBB-model outperforms other models when forecast upside is present and the result is statistically significant. On the other hand, when no forecast upside is present, the R-model, which does not use descending ranking criteria, outperforms other models, and the difference is statistically significant. We also find that adding descending ranking criteria to the R-model and ZF-model does not improve their Service-Cost Performance Index.

The interdisciplinary field of cognitive science has been and is becoming increasingly central within human factors and ergonomics (HF&E) and, since at the same time, there has long been a call for a more systems perspective in the area with a somewhat wider unit of analysis. This paper argues that the theoretical framework of distributed cognition would greatly benefit the application of HF&E to manufacturing and would offer a more holistic understanding of the interactions between different entities within a greater context, including the social, cultural and materialistic. We aim to characterize and analyse manufacturing as a complex socio-technical system from a distributed cognition perspective; focusing on the use, mediation and integration of different forms of representations, tools and artefacts in this domain. We present illustrative examples from authentic manual assembly, showing the cognitively distributed nature of the work, ranging from scaffolding strategies of the individual worker to the emergent properties of a whole assembly line. The paper further proposes and provides benefits of using a distributed cognition framework as a novel approach in the toolbox for the HF&E discipline, where it may have been found before, but the application to manufacturing has been absent.

This is an Open Access Article. It is published by Taylor & Francis under the Creative Commons Attribution 4.0 International Licence (CC BY). Full details of this licence are available at: http://creativecommons.org/licenses/by/4.0/