Forecasting and aggregate planning application – a case study of a small enterprise in Indonesia

Oey, Elia; Wijaya, Williem Artono; Hansopaheluwakan, Scherly

doi:10.1504/ijpmb.2020.10025874

Cited by 5 publications

(8 citation statements)

References 18 publications

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“…Most of the SMEs have basic frameworks and techniques that are fit for quick reaction to consumer requests. In this way, SMEs are a vital piece of this chain (Gupta and Garg, 2012; Jain et al , 2014; Oey et al , 2020).…”

Section: Literature Reviewmentioning

confidence: 99%

Design of an intelligent decision-making system for maintenance practices using fuzzy inference system in northern Indian SMEs

Sidhu

Singh

Ahuja

2020

JQME

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PurposeThe paper aims to analyze the significance of key maintenance practices in effective implementation of the performance parameters in Northern Indian small and medium-sized enterprises (SMEs).Design/methodology/approachThe present study deploys a fuzzy inference approach (fuzzy logic toolbox) to test the effective implementation of maintenance practices in SMEs. The significant maintenance factors are defined from applicable literature for this reason and validated by industry experts.FindingsA model built into a fuzzy rule viewer and a surface view tool built into a fuzzy toolbox in MATLAB has highlighted the successful implementation of maintenance practices in Indian SMEs. The study highlights that corrective maintenance, general maintenance, preventive maintenance and breakdown maintenance problems have emerged as important indicator variables for effective synergistic implementation of maintenance practices in northern Indian SMEs.Originality/valueAn output assessment model is developed using a fuzzy set theory for maintenance practices, where performance evaluation is significant to the overall performance of SMEs.

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Section: Literature Reviewmentioning

confidence: 99%

Design of an intelligent decision-making system for maintenance practices using fuzzy inference system in northern Indian SMEs

Sidhu

Singh

Ahuja

2020

JQME

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“…Most organisations attempt to generate an effective APP that meets customer demand and has minimum total costs. APP was studied and researched in terms of demand and supply planning to enhance its cost and productivity by examining seven common forecasting tools for demand planning side and exercising classical chase and level aggregate planning strategy for the supply planning side [2].…”

Section: Aggregate Production Planningmentioning

confidence: 99%

“…APP is a process by which decision-maker decides the suitable levels of capacity, production, subcontracting, inventory, stock-outs, and pricing over 3-18 months that can deal with uncertain customer requirements. Most organisations generate APP by considering minimise total costs: (1) Production costs that are related to purchasing materials and overhead, (2) Costs that are associated with changes in production rate such as hiring and firing costs and overtime compensation, and (3) Costs that are related to inventory such as holding and ordering costs. Fuzziness of data for an APP has been an important, challenging, and incentive working area for researchers and also one of the difficult issues that decisionmakers have to face in planning.…”

Section: Introductionmentioning

confidence: 99%

Integrated Possibilistic Linear Programming with Beta-Skewness Degree for a Fuzzy Multi-Objective Aggregate Production Planning Problem Under Uncertain Environments

Sutthibutr

Chiadamrong

2020

Fuzzy Information and Engineering

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This study proposes an improved Fuzzy Programming (FP) approach to optimise multi-objective Aggregate Production Planning (APP) problem under uncertain environments. The proposed approach integrates the concept of Possibilistic Linear Programming (PLP) with Beta-Skewness Degree that decision-makers can manipulate the best level of data fuzziness as well as maintain such fuzziness in the optimisation process (by not turning it to deterministic data too early). The effectiveness of the proposed approach is demonstrated through a case study by minimising the highest overall deviation from the ideal solution of total costs under imprecise operating costs, customer demand, labour level, and machine capacity. Our comparative result clearly shows that the obtained solution outperforms the solutions from traditional defuzzification methods. The proposed approach also helps decision-makers not only to know and optimise the most likely situation, but also realise the outcomes in the optimistic and the pessimistic business situations so that decision makers can prepare and take necessary actions for future uncertainty.

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“…Increasing pressures for ensuring customer satisfaction have necessitated the strategic focus should be on cost reduction, increased productivity, reliability and deliveries to meet the challenges of today’s competitive environment (Gonzalez-Aleu et al , 2018). Thus, manufacturing enterprises need to attain high quality and performance levels in all business functions to satisfy the stringent requirements posed by global competitiveness (Bai et al , 2019; Oey et al , 2020).…”

Section: Introductionmentioning

confidence: 99%

“…Most SMEs have simple structures and techniques that are capable of reacting quickly to customer demands. SMEs are thus a crucial part of this chain (Gupta and Garg, 2012; Jain et al , 2014; Oey et al , 2020).…”

Section: Introductionmentioning

confidence: 99%

An empirical investigation of maintenance practices for enhancing manufacturing performance in small and medium enterprises of northern India

Sidhu

Singh

Ahuja

2021

JSTPM

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Purpose This paper aims to assess the contributions of maintenance practices and extract various significant factors that influence the implementation of maintenance practices in northern Indian small and medium-sized enterprises’ (SMEs) business performance. Design/methodology/approach In the current study, 216 north Indian SMEs have been extensively surveyed to assess the contributions of different maintenance practices implementation dimensions and manufacturing performance attributes through different statistical techniques. Analysis of variance (ANOVA) was used to statistically validate the hypotheses, while Levene’s experiment and Wilk–Shapiro tests were used to confirm ANOVA’s assumptions. Finally, the discriminating validity test extracts highly successful and moderately successful organizations. Findings The present research aims to evaluate the contributions of different maintenance practices implementation dimensions on SMEs’ manufacturing performance attributes. The study highlights that strategic maintenance practices such as corrective maintenance (CM), general maintenance issues, preventive maintenance (PM) issues and predictive maintenance (Pd.M) initiatives have enhanced overall equipment effectiveness, overall business performance, quality, cost optimization, safety, delivery and morale in SMEs. Originality/value The study validates the capabilities of maintenance practices toward significant improvements of various implementation dimensions such as breakdown maintenance issues, general maintenance issues, PM issues, Pd.M issues, CM issues, computer maintenance management system issues, maintenance scheduling issues and total productive maintenance issues. The study reveals significant implications for SMEs for realizing significantly improved manufacturing performance through strategic maintenance initiatives.

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Forecasting and aggregate planning application – a case study of a small enterprise in Indonesia

Cited by 5 publications

References 18 publications

Design of an intelligent decision-making system for maintenance practices using fuzzy inference system in northern Indian SMEs

Design of an intelligent decision-making system for maintenance practices using fuzzy inference system in northern Indian SMEs

Integrated Possibilistic Linear Programming with Beta-Skewness Degree for a Fuzzy Multi-Objective Aggregate Production Planning Problem Under Uncertain Environments

An empirical investigation of maintenance practices for enhancing manufacturing performance in small and medium enterprises of northern India

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