Search results

Proposing an improved model for evaluating criticality of non-value added (waste) in operation is necessary for realizing sustainable manufacturing practices. The purpose of this paper is concerning on improvement of the decision support model for evaluating risk criticality lean waste occurrence by considering the weight of modified FMEA indices and the influence of waste-worsening factors causing the escalation of waste risk magnitude.

Integration of entropy and Taguchi loss function into decision support model of modified FMEA is presented to rectify the limitation of previous risk reprioritization models in modified FMEA studies. The weight of the probability components and loss components are quantified using entropy. A case study from industry is used to test the applicability of the integration model in practical situation.

The proposed model enables to overcome the limitations of using subjective determination on the weight of modified FMEA indices. The inclusion of the waste-worsening factors and Taguchi loss functions enables the FMEA team to articulate the severity level of waste consequences appropriately over the use of ordinal scale in ranking the risk of lean waste in modified FMEA references.

When appraising the risk of lean waste criticality, ignorance on weighting of FMEA indices may be inappropriate for an accurate risk-based decision-making. This paper provides insights to scholars and practitioners and others concerned with the lean operation to understand the significance of considering the impact of FMEA indices and waste-worsening factors in evaluating criticality of lean waste risks.

The method adopted is for quantifying the criticality of lean waste and inclusion of weighting of FMEA indices in modified FMEA provides insight and exemplar on tackling the risk of lean waste and determining the most critical waste affecting performability of company operations.

Integration of the entropy and Taguchi loss function for appraising the criticality of lean waste in modified FMEA is the first in the lean management discipline. These findings will be highly useful for professionals wishing to implement the lean waste reduction strategy.

In recent years, halal food industries are facing a high level of competition. The growing demand for halal food means firms are working hard to improve quality and reduce halal food defects. The purpose of this study is to propose a halal-based six sigma (SS) framework that could be used to reduce halal food defects and improve compliance.

The proposed halal six sigma (HSS) framework has five phases based on the define-measure-analyse-improve-control (DMAIC) approach. The proposed framework also integrates halal assurance system requirements into HSS to ensure compliance. Tools used in the proposed model include SIPOC tools, Pareto diagram, root cause analysis and the improvement process flows. A case study in a chicken meat company is used to test and validate the proposed framework. In case of study research, brainstorming was used to review an initial proposed framework and focus group discussions were used to determine feasible improvement actions.

The results showed that the proposed HSS framework could be effective to detect and reduce the halal defects and lower the halal defect costs. By adopting the framework, the case firm was able to lower halal defect costs significantly and increase the SS level.

SS approach can be designed and adapted to specific food industry. HSS framework could provide a systematic approach to reduce halal food defects and sustain the improvement efforts. The proposed HSS framework is also easy to use to understand halal critical points and improve halal compliance.

This study proposed a HSS framework that can be adopted to reduce halal food defects and costs. This proposed framework will benefit the halal food industry intending to realize zero halal food defects and lower production costs. The limited number of publications in the research theme of halal food defects show that there is a significant gap in the existing body of knowledge.

The demand for halal food products is increasing globally. However, fraudulent activities in halal products and certification are also rising. One strategy to ensure halal integrity in the food supply chain is applying halal blockchain technology. However, to date, a few studies have assessed the factors and variables that facilitate or hinder the adoption of this technology. Thus, this study aims to assess the significant factors and variables affecting the adoption of halal blockchain technology.

A Delphi-based approach, using semi-structured interviews, was conducted with three food companies (chicken slaughterhouses, milk processing plants and frozen food companies). The cognitive best–worst method determines the significant factors and variables to prioritise halal blockchain adoption decisions.

The results showed that the most significant factors were coercive pressure and halal strategy. Nineteen variables were identified to establish a valid hierarchical structure for halal blockchain adoption in the Indonesian food industry. The five significant variables assessed through the best–worst method were demand, regulator, supply side, sustainability of the company’s existence and main customers.

The proposed halal blockchain decision structure can assist food companies in deciding whether to adopt the technology.

This study proposes 19 variables that establish a valid hierarchical structure of halal blockchain adoption for the Indonesian food industry.

Indonesia has the largest Muslim population in the world and represents a significant global-market opportunity for halal food producers. Surprisingly, halal-food consumption in Indonesia remains under-researched. Thus, this study aims to investigate the factors influencing consumers’ halal-food consumption, using an extended theory of planned behaviour (TPB) model.

Data were collected through a self-administered questionnaire distributed among 418 consumers in Surabaya, Indonesia. Multiple regression analysis was used to describe the TPB relationship and halal-food consumption.

This study successfully extended the TPB to include additional predictors: perceived awareness, habit, religious self-identity (RSI), moral obligations and trust to determine consumers’ intention in halal-food consumption. Attitudes, RSI and moral obligations were significant predictors of intention to consume halal food.

The findings can be used by the government and food producers to target specific factors, especially positive attitudes, RSI and moral obligations. Indonesia Ulama Council (Majelis Ulama Indonesia), the food industry and the media play a critical role in sustaining consumers’ positive attitude towards halal-food consumption. It is critical for food manufacturers to tailor their marketing strategies and consider promoting Islamic dietary rules when promoting their food products.

To the best of the authors’ knowledge, this study is one of the first attempts to investigate the determinants of halal-food consumption, using an extended TPB in Indonesia.

Halal food market has grown significantly over the years. As consumers are becoming more aware of the significance of halal food products and certification, food industries will benefit from a model that controls and assures halal food production. Quality function deployment (QFD) is a tool to support product design and improve food quality systems. Thus, the purpose of this study is to propose a multi-phased QFD model to identify key processes and prioritise programmes to improve halal food production.

The matrix in the first phase was designed using the halal assurance system (HAS) requirements and the set of production process. The relationships between HAS requirements and a set of halal critical factors [i.e. raw material (chicken), workers, procedures and documentation, equipment and premises] were established in the second phase. In the final phase, potential problems and improvement programmes arising under each critical halal phase were identified. The QFD model was developed and applied in a chicken processing plant in Indonesia.

In Matrix 1, slaughtering, meat processing and meat delivery were identified as the key process, whilst equipment, procedures and documentation and workers were determined as the most critical halal factors in Matrix 2. The final phase of the QFD approach assisted the chicken processing plant in reducing potential issues by identifying key improvement programmes. The prioritisation of improvement programmes also supports the company in decision-making and allocating their resources accordingly.

The multi-phased QFD model can be designed and adapted to specific food industry. It can be used to assure halal food production and inform food industry which area to prioritise and to allocate resources accordingly. The improvement of halal food production will assist food companies to target and access international markets.

This study proposed a new multi-phased QFD model that can be used as a halal food assurance and prioritisation tool by the food industry. This model will benefit food industry intending to implement halal assurance scheme in their process, halal auditors and policymakers.

A traceability system is a key success factor in global food trade, but implementing it in vegetable oil industry is one of the most difficult undertakings in food supply chain management. This study aims to (1) identify typical operational barriers in the implementation of bulk-liquid traceability system in the Indonesian vegetable oil industry by considering the perspective of experts and (2) model the relationship between the barriers structurally in order to improve the reliability of the traceability system.

To do so, data from in-depth interviews with experts were examined by using content analysis. Then the authors used a combination of decision-making trial and evaluation laboratory (DEMATEL), interpretive structural modelling (ISM) and matrice d'impacts croisés multiplication appliqué un classement (MICMAC) to construct the hierarchical model and to cluster the typical barriers based on their driving power and dependence power.

In total, 20 typical traceability barriers along the internal chain (supplier-input-process-output-customer) were identified. The interrelationships between these barriers were modeled in a hierarchical structure, seeking to answer why it is difficult to implement a traceability system and what actions should be taken to remove these barriers.

The model can shed light on how to manage barriers in bulk-liquid food commodity industry, especially in the vegetable oil industry. An action map has been proposed to overcome the operational barriers. This model will also help tracing the critical points of the traceability system.

Compared to other food commodities, operational barriers in vegetable oil chain has never been studied specifically. In fact, there are many operational aspects that hinder traceability. The Indonesian context entails social, economic and environmental factors as well, so it can inform decision-makers in formulating an action map.