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The quality of haemodialysis process is a prime concern in renal care. This study, carried out at one of the leading Hospitals in Central India, providing kidney care and dialysis, aims to identify areas in the haemodialysis unit needing special attention, to improve process quality and ensure better patient welfare.

The failure mode and effects analysis (FMEA) approach included: deciding haemodialysis process requirements, identifying potential causes of process failure and quantifying associated risk with every cause. Suitable actions were then implemented to reduce the occurrence and improving the controls, thereby reducing risk. The study used primary data generated and monitored over the period: July‐December 2008.

Adopting proper checklists for work monitoring, providing training to enhance patient and staff awareness; led to reduced process errors, mitigating overall risks, eventually resulting in effective patient care.

The quantification of risk associated with every likely failure is subjective.

The findings have a great significance in relation to kidney patients' welfare. The process areas which may get compromised are highlighted so that they get due attention. Error proofing makes the process “robust”, reducing its vulnerability.

This study provides a microscopic error proofing approach to haemodialysis process using a proven engineering tool, FMEA, ensuring quality improvement. This approach can also be extended to cover other hospital activities.

This paper presents a proposal of adaptation of the failure mode and effect analysis method to analyze wastes and define priorities for actions aimed at minimizing or eliminating these wastes based on the criteria of severity, occurrence and detection.

The proposition was developed in parallel to the implementation of a lean production system of a manufacturing company. A pilot application of the proposal was based on the analysis of a flow of information for order processing.

Application of the proposed procedure results in a classification of levels of priority for waste reduction of the analyzed waste modes. Following this procedure, high priority will be given to actions focused on the elimination or minimization of the most common causes of the most severe waste modes.

Prioritization of actions to minimize waste is essential to sustain lean production systems. However, identifying the wastes most in need of attention is not always straightforward and methods presented in the literature to evaluate leanness do not focus on waste reduction prioritization. Adoption of the proposed technique can certainly aid planning implementation and improvement of lean production programs, and in the end, it can contribute to the effectiveness and sustainability of lean production systems.

The purpose of this paper is to present a modified failure mode and effects analysis (FMEA) in order to make the assignment of the scores for the occurrence factor more robust, and to link the FMEA chart directly to the maintenance activities.

A well-known clustering algorithm (i.e. K-means), along with a normalisation approach, are applied and compared for the assignment of the occurrence scores. Subsequently, the relationship between failures and maintenance operations is made explicit by a correlation matrix. Finally, the K-means algorithm is applied to the maintenance operations again in order to sort them into priority classes.

It is found that this revised FMEA approach improves the standard one due to its more rigorous mathematical formulation and lean applicability in real operating environments.

The novel approach may be improved by a deeper statistical analysis and/or applying the fuzzy theory.

A real case study is introduced in order to show the applicability of this approach to the quality control of a blow moulding process. It is found that this approach reveals a high potentiality for dealing with real issues.

The paper provides a further step towards bridging the gap between theory and practical application of the FMEA approach.

Learning outcomes are as follows: students will discover the importance of process orientation in management; students will determine the root cause of the problem by applying root cause analysis technique; students will identify the failure modes, analyze their effect, score them on a scale and prioritize the corrective action to prevent the failures; students will analyze the processes and propose error-proof system/s; and students will analyze organizational culture and ethical issues.

Purpose: This case study is intended as a class-exercise, for students to discover the importance of process-orientation in management, analyze the ethical dilemma in health care and to apply quality management techniques, such as five-why, root cause analysis, failure mode and effect analysis (FMEA) and error-proofing, in the management of the health-care and service industry. Design/methodology/approach: A voluntary reporting of a case of “radiation overdose” in a hospital’s radio therapy treatment unit, which led to an ethical dilemma. Consequently, a study was conducted to establish the causes of the incident and to develop a fail-proof system, to avoid recurrence. Findings: After careful analysis of the process-flow and the root causes, 25 potential failure modes were detected and the team had assigned a risk priority number (RPN) for each potential incident, selected the top ten RPNs and developed an error-proofing system to prevent recurrence. Subsequently, the improvement process was carried out for all the 25 potential incidents and a new control mechanism was implemented. The question of ethical dilemma remained unresolved. Research limitations/implications: Ishikawa diagram, FMEA and Poka-Yoke techniques require a multi-disciplinary team with process knowledge in identifying the possible root causes for errors, potential risks and also the possible error-proofing method/s. Besides, these techniques need frank discussions and agreement among team members on the efforts for the development of action plan, implementation and control of the new processes. Practical implications: Students can take the case data to identify root cause analysis and the RPN (RPN = possibility of detection × probability of occurrence × severity), to redesign the protocols, through systematic identification of the deficiencies of the existing protocols. Further, they can recommend quality improvement projects. Faculty can navigate the case session orientation, emphasizing quality management or ethical practices, depending on the course for which the case is selected.

MBA or PG Diploma in Management – health-care management, hospital administration, operations management, services operations, total quality management (TQM) and ethics.

Teaching Notes are available for educators only.

CSS 9: Operations and Logistics.