Supply chain performance measurement and improvement system

Modelling supply chain risks and their impacts on the performance of the sago starch agro-industry

Purpose

Supply chain risks (SCRs) have uncertainty and interdependency characteristics that must be incorporated into the risk assessment stage of the SCR management framework. This study aims to develop SCR networks and determine the major risk drivers that impact the performance of the sago starch agro-industry (SSA).

Design/methodology/approach

The risk and performance variables were collected from the relevant literature and expert consultations. The Bayesian network (BN) approach was used to model the uncertain and interdependent SCRs. A hybrid method was used to develop the BN structure through the expert’s knowledge acquisitions and the learning algorithm application. Sensitivity analyses were performed to examine the significant risk driver and their related paths.

Findings

The analyses of model indicated several significant risk drivers that could affect the performance of the SSA. These SCR including both operational and disruption risks across sourcing, processing and delivery stage.

Research limitations/implications

The implementation of the methodology was only applied to the Indonesian small-medium size sago starch agro-industry. The generalization of findings is limited to industry characteristics. The modelled system is restricted to inbound, processing and outbound logistics with the risk perspective from the industry point of view.

Practical implications

The results of this study assist the related actors of the sago starch agro-industry in recognizing the major risk drivers and their related paths in impacting the performance measures.

Originality/value

This study proposes the use of a hybrid method in developing SCR networks. This study found the significant risk drivers that impact the performance of the sago starch agro-industry.

Entropy-Based Lean, Energy and Six Sigma Approach to Achieve Sustainability in Manufacturing System

This work proposes a Value Stream Mapping (VSM) to be used in manufacturing industry that combines Lean, Energy and Six-Sigma methodologies. Lean's VSM tool is amended to energy VSM so that the value-added and non-value-added approach can be used to determine the energy use and waste. In order to identify the maximum rejection or rework at a workstation, an entropy-based mathematical model is developed and a Lean-Energy-Six Sigma Value Stream Mapping (LESSVSM) is presented. The model can be used in manufacturing at product level where temperature and energy can be measured from input to output. The model has been implemented on a manufacturing system containing four workstations. The proposed LESSVSM model will help to industry to become more sustainable as it can minimize energy and waste in the case of rework and rejection. This study presents a systematic approach which researchers and practitioners can apply for sustainable manufacturing.

Designing a sustainable integrated forward/reverse logistics network

Purpose

In recent years, governmental regulations and the pressure of non-governmental organizations have convinced corporations to consider sustainable issues in their decisions. A simultaneous design of forward and reverse logistics can keep us away from sub-optimality caused by tackling these two phases (forward and reverse logistics) separately.

Design/methodology/approach

Hence, this paper presents a new multi-objective mathematical model for integrated forward and reverse logistics regarding economic, environmental and social issues. A new hybrid multi-objective metaheuristic algorithm is developed to obtain a set of efficient solutions (Pareto solutions). The proposed algorithm hybridizes a well-known, non-dominated genetic algorithm (NSGA-II) with a simulated annealing algorithm.

Findings

To validate the algorithm, its results are compared to the obtained solutions from simple NSGA-II with respect to some comparison metrics. The numerical results show the efficiency of the proposed algorithm. Finally, concluding remarks and future research directions are provided.

Originality/value

By applying a model presented in this paper, one can reach to sustainable and integrated logistics network which considers forward and reverse flow of commodities simultaneously.