Kaizen event approach: a case study in the packaging industry

Employee's performance and Kaizen events' success: does supervisor behaviour play a moderating role?

Purpose

The study's goal was to identify the factors contributing to the practical completion of Kaizen events (KEs). The effect of the work-study man's characteristics, the supervisor's conduct and the autonomy of the Kaizen team are analysed in this study.

Design/methodology/approach

Data were collected from 249 respondents working in the manufacturing sector in India, mainly those who had been involved in Kaizen projects. Three-step procedures, namely, exploratory factor analysis, confirmatory factor analysis and partial least squares, have been applied to test the research hypotheses through structural equational modelling.

Findings

The exploratory factor analysis extracted in-role performance, creative performance and human aspect as latent variables explaining work-study man's performance (eigenvalue = 1). The study's findings indicate that the performance of work-study man (in-role, creative and human) and supervisors' conduct is directly related to the success of KEs. It was shown that supervisors might influence the outcomes of KEs only by moderating the human aspects. Additionally, the degree of autonomy of the Kaizen team was found having a significant positive relationship with the success of KEs.

Practical implications

The current study suggests that in-role and creative performance are prime assets of a work-study man. At the same time, the human aspect is a delicate issue that can affect the supervisor's behaviour. Therefore, the study implies that work-study men have the tactics and abilities to work with other co-workers to make a Kaizen project successful.

Originality/value

Although the significance of Kaizen projects has been widely emphasised, past research has failed to establish what factors contribute to the success of Kaizen efforts. Similarly, the supervisor's critical role has been highlighted several times. However, it is unclear how their conduct influences the relationship between work-study man's performance and the effectiveness of Kaizen projects. This study contributes significantly to organisational culture and human resource management by answering these questions.

Symbiotic relationship between robotics and Lean Manufacturing: a case study involving line balancing

Purpose

The present paper aims to demonstrate the potential of integration between industrial robotics and Lean Manufacturing (LM) approach to increase the efficiency of an assembly line.

Design/methodology/approach

Based on a case study performed in an Italian company, this paper reports a comparative analysis of the results produced on a line balancing study involving a semi-automated production line, aided by an industrial robot.

Findings

The results suggest the possibility of implementing industrial robotics in line balancing studies highlighting efficiency gains and idle reduction. Further, it also addresses some concepts directly related to industry 4.0, such as collaborative robotics, artificial intelligence, and lean automation.

Practical implications

Line balancing studies may include advanced robotics in order to extend traditional lean practices toward Digital LM.

Originality/value

This study adds contributions to the operational excellence literature, demonstrating the symbiosis between industrial robotics and LM practices.

Kaizen event process quality: towards a phase-based understanding of high-quality group problem-solving

Purpose

As a problem-solving tool, the kaizen event (KE) is underutilised in practice. Assuming this is due to a lack of group process quality during those events, the authors aimed to grasp what is needed during high-quality KE meetings. Guided by the phased approach for structured problem-solving, the authors built and explored a measure for enriching future KE research.

Design/methodology/approach

Six phases were used to code all verbal contributions (N = 5,442) in 21 diverse, videotaped KE meetings. Resembling state space grids, the authors visualised the course of each meeting with line graphs which were shown to ten individual kaizen experts as well as to the filmed kaizen groups.

Findings

From their reactions to the graphs the authors extracted high-quality KE process characteristics. At the end of each phase, that should be enacted sequentially, explicit group consensus appeared to be crucial. Some of the groups spent too little time on a group-shared understanding of the problem and its root causes. Surprisingly, the mixed-methods data suggested that small and infrequent deviations (“jumps”) to another phase might be necessary for a high-quality process. According to the newly developed quantitative process measure, when groups often jump from one phase to a distant, previous or next phase, this relates to low KE process quality.

Originality/value

A refined conceptual model and research agenda are offered for generating better solutions during KEs, and the authors urge examinations of the effects of well-crafted KE training.

Analysis of enablers for the digitalization of supply chain using an interpretive structural modelling approach

Purpose

Over the years, technology development has rationalized supply chain processes. The demand economy is disrupting every sector causing the supply chain to be more innovative than ever before. The digitalization of the supply chain fulfils this demand. Several technologies such as blockchain, big data analytics, 3D printing, Internet of things (IoT), artificial intelligence (AI), augmented reality (AR), etc. have been innovated in recent years, which expedite the digitalization of the supply chain. The paper aims to analyse the applicability of these technological enablers in the digital transformation of the supply chain and to present an interpretive structural modelling (ISM) model, which presents a sequence in which enablers can be implemented in a sequential manner.

Design/methodology/approach

This paper employed the ISM approach to propose a various levelled model for the enablers of the digital supply chain. The enablers are also classified graphically based on their driving and dependence powers using matrix multiplication cross-impact applied to classification (MICMAC) analysis.

Findings

The study indicates that the enablers “big data analytics”, “IoT”, “blockchain” and “AI” are the most powerful enablers for the digitalization of the supply chain and actualizing these enablers should be a topmost concern for organizations, which want to exploit new opportunities created by these technologies.

Practical implications

This study presents a systematic approach to adopt new technologies for performing various supply chain activities and assists the policymakers better organize their assets and execution endeavours towards digitalization of the supply chain.

Originality/value

This is one of the initial research studies, which has analysed the enablers for the digitalization supply chain using the ISM approach.

Kaizen transferability in non-Japanese cultures: a combined approach of total interpretive structural modeling and analytic network process

Purpose

The literature on Kaizen transferability to non-Japanese culture is still evolving. The results suggest that the relevant research is still at a descriptive and explanatory stage. This study aims to identify and prioritize the importance of significant Kaizen transferability factors in a non-Japanese culture.

Design/methodology/approach

A decision theory-based prescriptive analysis methodology was used to analyze identified Kaizen transferability success factors. Firstly, a list of Kaizen transferability factors was devised from the literature using a systematic literature review. Secondly, an integrated interpretative structure modeling and analytic network process approach were applied to generate preference among factors.

Findings

A framework with a prioritized Kaizen transferability success factors included, in ascending order, organization culture, employee participation, employee discipline, employee personal initiative, top management commitment, management enforcement, employee eagerness, management support and national culture and traditions.

Research limitations/implications

Managers and decision-makers would better understand where to direct their effort and attention to implement the Kaizen management philosophy to improve firm-level productivity. Although the factors studied in this research considered the Indonesian context, the proposed framework could be replicated and extended to include other cultures.

Originality/value

The present work contributes to the limited studies and documentation on Kaizen activities' transferability challenges and the Kaizen body of knowledge in developing countries. This study should help organizations in other developing countries, assimilate how to adopt and manage the Kaizen philosophy implementation by following the framework created in this research.

A hybrid model for ranking critical successful factors of Lean Six Sigma in the oil and gas industry

Purpose

The aim of this paper is to find and prioritise multiple critical success factors (CSFs) for the implementation of LSS in the oil and gas industry.

Design/methodology/approach

Based on a preselected list of possible CFSs, experts are involved in screening them with the Delphi method. As a result, 22 customised CSFs are selected. To prioritise these CSFs, the step-wise weight assessment ratio analysis (SWARA) method is applied to find weights corresponding to the decision-making preferences. Since the regular permutation-based weight assessment can be classified as NP-hard, the problem is solved by a metaheuristic method. For this purpose, a genetic algorithm (GA) is used.

Findings

The resulting prioritisation of CSFs helps companies find out which factors have a high priority in order to focus on them. The less important factors can be neglected and thus do not require limited resources.

Research limitations/implications

Only a specific set of methods have been considered.

Practical implications

The resulting prioritisation of CSFs helps companies find out which factors have a high priority in order to focus on them.

Social implications

The methodology supports respective evaluations in general.

Originality/value

The paper contributes to the very limited research on the implementation of LSS in the oil and gas industry, and, in addition, it suggests the usage of SWARA, a permutation method and a GA, which have not yet been researched, for the prioritisation of CSFs of LSS.