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The safety and reliability of oil transfer pipelines are crucial, as pipeline failures can severely affect the environment. As pipeline risk management is dynamic and uncertain, traditional maintenance approaches often fall short. This research paper proposes an Intuitive Fuzzy Computational Approach (IFCA) for oil transfer pipeline maintenance (RBM). To develop a targeted and nuanced maintenance plan, Failure Modes and Effects Analysis (FMEA) is employed. Pipeline equipment is hierarchically organised according to their failure mode criticality, which guides maintenance design. This paper leverages the context of an Interval Valued Intuitionistic Fuzzy (IVIF) environment to streamline the hierarchical classification of oil transmission pipeline instruments. The objectives are threefold: (1) to develop an intuitionistic fuzzy risk assessment model, (2) to design a modified algorithm for maintenance prioritisation, and (3) to develop a decision support system. Additionally, the research incorporates the IVIF-SWARA method to enable flexible adjustments in the alignment of the pipeline instruments. By addressing the specific challenges of oil transfer pipelines, this research aims to contribute to advancing the field of pipeline maintenance and risk management. The proposed RBM strategy, underpinned by the IFCA framework, is expected to enhance pipeline reliability and mitigate the risks associated with pipeline failures. Abbreviations: RBM: Risk-Based Maintenance; IFCA: Intuitionistic Fuzzy Computational Approach; FMEA: Failure Modes and Effects Analysis; IVIF: Interval Valued Intuitionistic Fuzzy; SWARA: Stepwise Weight Assessment Ratio Analysis; RCM: Reliability-Centered Maintenance; RBI: Risk-Based Inspection; CBM: Condition-Based Maintenance; IFS: Intuitionistic Fuzzy Set; HFPR: Hesitant Fuzzy Preference Relation; IVIFPHA: Interval-Valued Intuitionistic Fuzzy Power Heronian Aggregation; MCDM: Multi-Criteria Decision-Making; $ \textrm{S}{\textrm{C}_{{O_i}}} $ S C O i : Accuracy Function of Occurrence; $ \textrm{S}{\textrm{C}_{{S_i}}} $ S C S i : Accuracy Function of Severity; $ K({\tilde{a}}) $ K ( a ~ ) : Failure Probability Index; $ L{W_D} $ L W D : Minimum Allowable Weight of The Failure Detection Index; WS, WO, WD: Weight Assigned to The Failure Outcome; $ \textrm{RP}{\textrm{V}_\textrm{j}} $ RP V j : Relative Priority Value; OREDA: The Offshore Reliable Data Handbook; IVIFPWHA: Interval-Valued Intuitionistic Fuzzy Power Weight Heronian Aggregation [ABSTRACT FROM AUTHOR]

Purpose – This paper aims to focus on duopolistic competition under dynamic price and production postponement for two differentiable products that share common product platform at a certain degree of product commonality. Design/methodology/approach – Both price and production postponement modelling are benchmarked according to their profit in order to investigate the product substitutability effect to the profit and also their appropriateness to different competition situations. In addition, dynamic property is applied to show the demand changes effect of both strategic decisions (price and production) against demand uncertainty. Findings – The results show that the pure price postponement is appropriate to be applied into highly customized products while pure production postponement to configurable products. Research limitations/implications – Price and production postponement decisions help managers to optimize product development as well as production strategy by considering demand and supply sides. Practical implications – Price and production postponements give alternative ways to managers for deciding on how to produce products as fighting product and mass customized product. Originality/value – Innovative price and production postponement models are the novelty of this paper. [ABSTRACT FROM AUTHOR]

Purpose – This paper aims to focus on production ramp up modeling on built-to-order (BTO) manufacturers facing customized demand. The general purpose is to present a novel approach to managing collaboration, by considering information exchange between the manufacturer and the supplier. Design/methodology/approach – The methodology applies feedback control mechanism to analyze supplier responsiveness and customer order decoupling point to represent the need for collaboration. A two-stage game is applied ahead of control system application to optimize the capacity decision, with the ultimate goal being profit maximization. Findings – The results show that a higher product commonality degree gives more opportunity for quick response BTO supply chains, which are managed by feedback control, and at the same time to possibly mitigate the bullwhip effect caused by demand information noise. Research limitations/implications – The analytical model here focused on one product family development, so the applicability of the proposed model to the whole product portfolio should be investigated in the future. Practical implications – This paper helps the manufacturer to act optimally by considering the possibility of information exchange with the supplier and deciding on the product commonality degree, in taking into account the customer's lead time requirement. Originality/value – A control system model of "BTO Supply Chain" is proposed by including product commonality and response analysis in the simulation model. Furthermore, a contribution to collaborative supply chains is shown by applying a synchronized supply model to represent supplier and manufacturer communication. [ABSTRACT FROM AUTHOR]