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The purpose of this paper is to present the application of a procedure for the quality control of stainless steel tubes produced for automotive exhaust systems from a leading company in the steel sector, based on the Delphi method in accordance with the ISO/TS 16949:2009 and the ISO 9000:2008. Using Delphi methodology, it was possible to identify the main problems in the production lines object of the study, the main defects and their causes. Statistical methods were used to monitor process compliance and capacity. The panel of experts involved in Delphi method was able to identify causes of non‐compliance and suggest corrective actions.

The quality procedure implemented involves the application of the Delphi method and the ISO/TS 16949:2009 standard in conjunction with ISO 9000:2008 to the production line of welded tubes for exhaust systems. The statistical methods used to monitor the process were mainly control charts. Capability index, Cp and Cpk, were used to measure the process attitude to produce compliant outputs. Dimensional data were acquired by non‐destructive testing on diameters and X‐R charts were used to graphically represent the process state of control. Destructive tests were performed to monitor the welding quality and P‐chart were used to assess the proportion of nonconforming units.

In this work, a procedure was developed in order to characterize the production process of TXM tubes realized in the line 31 of the leader company plant. The use of Delphi methodology, in order to incorporate experts opinions in the quality control of stainless steel tubes, was one of the main points of this work. The panel of experts worked together to identify process issues, define their causes and propose corrective actions. The paper provides an overview about the quality approach of one of the world's largest companies in the production of steel and shows also how the statistical tools are used in order to manage process behavior.

The value of this paper is to illustrate an innovative approach to a real life quality problem; it demonstrates how the application of qualitative and quantitative quality instruments in accordance with technical specification can help in increasing and maintaining product compliance and in optimizing the management of resources.

The purpose of this paper is to propose an integrated model of decision support system (DSS), artificial neural network, information and communication technologies and statistical process control (SPC) to facilitate agreement by different stakeholders with special interests to commit to the decision that will be taken to stop the production line when something goes wrong somewhere in a supplier network environment.

A DSS is proposed to capture exceptional signals from source on deterioration of product quality to alert preventive actions needed before the problems are getting out of hand. The supervisors are given a set of guidelines to support making the decision. Real‐time SPC and rule‐based decision support procedures are used to trigger pre‐defined exceptional signals for forwarding to the most appropriate person (the knowledge holder in the problem domain) to make a decision to stop the line. All servers in all remote sites are internet‐connected and provide real‐time quality data to the regional supply chain manager. A case study is described to show how this is implemented in a lens manufacturing company.

A significant improvement in quality level can be achieved by holding the knowledge worker accountable for making the decision to stop the production line rather than made by default as is with most traditional operations.

To provide a concept to structure activities for decision support so that the persons responsible for making the decision to stop the production line is held accountable by all stakeholders.

Practitioners can replicate the approach used in this paper to their own situations involving decisions to be made to address un‐structured problems and unclear responsibilities.

This paper studies organizational change following a shift in an industry environment, in the context of how a focused factory adapts to a change in its manufacturing objectives. We use the organizational nature of production operations to suggest that the effectiveness of adaptation will depend on how well the manufacturing requirements of the new objectives match manufacturing capabilities at the production line level. We test our hypotheses using primary data from the Hartselle, Alabama compressor manufacturing focused factory of the Copeland Corporation. The results suggest that factors that influence adaptability derive from individual and organizational competence, and that the direction and extent of their influence depends on the systemic nature of the operational activity concerned. The results highlight roles of carefully designed complexity in operations and of process-oriented decision making on the shop floor in successful adaptation. This work contributes to our understanding of how business organizations overcome constraints to change.

This study aims to investigate how to identify and address production levelling problems in assembly lines utilising an intensive manual workforce when higher productivity levels are urgently requested to meet market demands.

A mixed-methods approach was used in the research design, integrating case study analysis, interviews and qualitative/quantitative data collection and analysis. The methodology implemented also introduces to the literature on operational performance a novel combination of data analysis methods by introducing the use of the Natural Language Understanding (NLU) methods.

First, the findings unveil the impacts on operational performance that transportation, limited documentation and waiting times play in assembly lines composed of an intensive workforce. Second, the paper unveils the understanding of the role that a limited understanding of how the assembly line functions play in productivity. Finally, the authors provide actionable insights into the levelling problems in manual assembly lines.

This research supports industries operating assembly lines with intensive utilisation of manual workforce to improve operational performance. The paper also proposed a novel conceptual model prescriptively guiding quick and long-term improvements in intensive manual workforce assembly lines. The article assists industrial decision-makers with subsequent turnaround strategies to ensure higher efficiency levels requested by the market.

The paper offers actionable findings relevant to other manual assembly lines utilising an intensive workforce looking to improve operational performance. Some of the methods and strategies examined in this study to improve productivity require minimal capital investments. Lastly, the study contributes to the empirical literature by identifying production levelling problems in a real context.

Shop floor control systems are generally major points of discussion in production planning and control literature. The purpose of this paper is to investigate how lean production control principles can be used in a make-to-order (MTO) job shop, where the volume is typically low and there is high variety. This paper examines the procedures involved in implementing a constant work-in-process (CONWIP)/Kanban hybrid system in the shop floor environment and also provides insights and guidelines on the implementation of a hybrid system in a high-variety/low-volume environment.

The authors review literature on Kanban, CONWIP, and CONWIP/Kanban hybrid systems to analyze how lean production control principles can be used in a MTO job shop. The second part focuses on the process of implementation. Using a case study of a manufacturer of electromechanical components for valve monitoring and controls, the paper describes how the operation is transformed by for more efficient shop floor control systems. Real experiments are used to compare pre- and post-improvement performance.

The study shows that the proposed hybrid Kanban-CONWIP system reduced the cycle time and achieved an increase of 38 percent in inventory turnover. The empirical results from this pilot study provide useful managerial insights for a benchmarking analysis of the actions to be taken into consideration by companies that have similar manufacturing systems.

The statistic generalization of the results is impossible due to the use of a single case method of study.

This paper provides insights and guidelines on the implementation of a hybrid system in a high-variety/low-volume environment. The literature on real applications of hybrid CONWIP/Kanban by case study is limited.

ORGANIZATIONS operating in a city which earned the phrase ‘Shipshape and Bristol fashion’ have a formidable reputation to maintain. So much is expected of them. One at least need have no fears on those grounds if a first visit to its Annual Conference is typical of previous ones. It is the Department of Work Study and Staff Training of the Engineering Employers' West of England Association.

The aims of this paper is to investigate simulation‐based optimisation and stochastic dominance testing while employing kanban‐like production control strategies (PCS) operating dedicated and, where applicable, shared kanban card allocation policies in a multi‐product system with negligible set‐up times and with consideration for robustness to uncertainty.

Discrete event simulation and a genetic algorithm were utilised to optimise the control parameters for dedicated kanban control strategy (KCS), CONWIP and base stock control strategy (BSCS), extended kanban control strategy (EKCS) and generalised kanban control strategy (GKCS) as well as the shared versions of EKCS and GKCS. All‐pairwise comparisons and a ranking and selection technique were employed to compare the performances of the strategies and select the best strategy without consideration of robustness to uncertainty. A latin hypercube sampling experimental design and stochastic dominance testing were utilised to determine the preferred strategy when robustness to uncertainty is considered.

The findings of this work show that shared GKCS outperforms other strategies when robustness is not considered. However, when robustness of the strategies to uncertainty in the production environment is considered, the results of our research show that the dedicated EKCS is preferred. The effect of system bottleneck location on the inventory accumulation behaviour of different strategies is reported and this was also observed to have a relationship to the nature of a PCS's kanban information transmission.

The findings of this study are directly relevant to industry where increasing market pressures for product diversity require operating multi‐product production lines with negligible set‐up times. The optimization and robustness test approaches employed in this work can be extended to the analysis of more complicated system configurations and higher number of product types.

This work involves further investigation into the performance of multi‐product kanban‐like PCS by examining their robustness to common sources of uncertainties after they have been initially optimized for base scenarios. The results of the robustness tests also provide new insights into how dedicated kanban card allocation policies might offer higher flexibility and robustness over shared policies under conditions of uncertainty.

In a packaging olives manufacturing system, the drained weight of the product plays a decisive role in customer’s satisfaction as well as in financial saving for the organization. The purpose of this study is to minimize the variation of the drained weight of olives in the production system to avoid the negative consequences.

The research develops a practical implementation step-by-step of Six Sigma define, measure, analyze, improve and control (DMAIC) in reducing the variation of the drained weight of olives.

Data analysis was used at various phases of the project to identify the root causes of rejection and rework. As a result of the necessary interventions and actions to optimize the manufacturing process, the standard deviation of drained weight was significantly reduced by 51.02%, with a 99.97% decrease in the number of parts per million defectives. Thus, the yield of the production process was improved by 8.24%. The estimated annual savings from this project were US$ 228,000 resulting from reduced rejection and rework.

This research may be used in packaging olives production systems as a tool for managers and engineers planning to increase productivity and efficiency while also improving product quality. The study also provided the organization with helpful actions that will be used to guide future Six Sigma operations management on the system. Thus, practical guidelines and solutions are provided.

In this project, for the first time, the Six Sigma methodology has been applied to solve a real-world problem in the packaging olives manufacturing system and to show that the DMAIC approach may assist to improve the efficiency of their operations and hence contribute to their quest toward continuous improvement.

An analysis of the US border manufacturing industry revealed that, while a plentiful supply of inexpensive labor is available, there are high levels of absenteeism and turnover. This in turn has affected this industry’s ability to implement lean and agile manufacturing production environments. It was argued that lower inventory levels and quicker response time to market fluctuations are required for these manufacturers to stay competitive. Yet, without careful consideration of the idiosyncrasies of the infrastructure, the change to leaner and more agile manufacturing could destroy some of these plants. The high levels of absenteeism and turnover, which have a direct bearing on the low and variable product yield rates, could cause an agile and lean production system to fail. Yet this research has shown that a recursive, pull‐type production control system that will meet the required daily quota and minimize inventory while accounting for high levels of absenteeism and turnover that directly affect workstation yield rates would be advantageous. That is, a US border manufacturer can become leaner and more agile in spite of the drawbacks that are germane to the US border manufacturing industry.

Our objective, when reporting on a series of research projects conducted between our two management centres, UMIST and INSEAD, was firstly to comment upon our European experiences against the background of the changing world. Our second concern was to express, in terms acceptable to us, that production management is at the core of our interest and that, as researchers, we could not accept the great technical predominance that has characterized the teachings of those concerned with production technology. As observers of the changes in the social framework we are aware of the attention given to production problems by sociologists, psychologists and industrial anthropologists and, like interested technicians, we follow and occasionally applaud, their discoveries. Like those with day‐to‐day production problems we try not to be carried away with novelty and, as a result, one of our major tasks has been to remain ‘in touch’ with those in production departments throughout Europe, who have the responsibility of earning the nation's living. It is, after all, these people who are the concern of governments, unions and managers.