A model-driven decision approach to collaborative planning and obsolescence for manufacturing operations

Abstract

Purpose The purpose of this paper is to present the model-driven decision support system (DSS) for small and medium manufacturing enterprises (SMMEs) that actively participates in collaborative activities and manages the planned obsolescence in production. In dealing with the complexity of such demand and supply scenario, the optimisation models are also developed to evaluate the performance of operations practices. Design/methodology/approach The model-driven DSS for SMMEs, which uses the optimisation models for managing and coordinating planned obsolescence, is developed to determine the optimal manufacturing plan and minimise operating costs. A case application with the planned obsolescence and production scenario is also provided to demonstrate the approach and practical insights of DSS. Findings Assessing planned obsolescence in production is a challenge for manufacturing managers. A DSS for SMMEs can enable the computerised support in decision making and understand the planned obsolescence scenarios. The causal relationship of different time-varying component obsolescence and availability in production are also examined, which may have an impact on the overall operating costs for producing manufactured products. Research limitations/implications DSS can resolve and handle the complexity of production and planned obsolescence scenarios in manufacturing industry. The optimisation models used in the DSS excludes the variability in component wear-out life and technology cycle. In the future study, the optimisation models in DSS will be extended by taking into the uncertainty of different component wear-out life and technology cycle considerations. Originality/value This paper demonstrates the flexibility of DSS that facilitates the optimisation models for collaborative manufacturing in planned obsolescence and achieves cost effectiveness.

Collaboration between supply chain partners: when does it matter? Evidence from collaborative profiles

“…In general, this framework is more comprehensive and can lead to better success. Other literature (Kuik and Diong, 2019;Nakano, 2009) discussed steps to execute collaborative planning. Researchers (Gupta and Andersen, 2018;Liu et al, 2020;Nyaga et al, 2010) also demonstrated how to measure collaboration performance/intensity based on the elements described above.…”

A decision support system to evaluate the quality and warranty policies for remanufactured products

“…In this study, the system architecture of a model driven DSS is divided into the hardware infrastructure and software application packages. The system design is adopted from Kuik and Diong (2019). Basically, there are three architecture modules in the system.…”

“…For implementation, the four-phase decision making model as adopted from Kuik and Diong (2019) is applied. The decision model has four phases including intelligence, design and choice and implementation phases.…”

Industry 4.0‐Driven Development of Optimization Algorithms: A Systematic Overview

“…It was hard to find a suitable partnership to develop a nonhierarchical network, but Industry 4.0 tools seem to support the CMM structure [19]. A network needs to be organized that integrates the various customer-supplier and design-support aspects most effectively in order to increase the efficiency of the business and production [20].…”