•Harnessing optimum value from industrial data increased in the last two decades.•A detailed review of “big data” application in operations/SC management processes.•Proposed (Value-adding – V5) ...framework for operation/SC management.
Big data is increasingly becoming a major organizational enterprise force to reckon with in this global era for all sizes of industries. It is a trending new enterprise system or platform which seemingly offers more features for acquiring, storing and analysing voluminous generated data from various sources to obtain value-additions. However, current research reveals that there is limited agreement regarding the performance of “big data.” Therefore, this paper attempts to thoroughly investigate “big data,” its application and analysis in operations or supply-chain management, as well as the trends and perspectives in this research area. This paper is organized in the form of a literature review, discussing the main issues of “big data” and its extension into “big data II”/IoT–value-adding perspectives by proposing a value-adding framework.
The research approach employed is a comprehensive literature review. About 100 or more peer-reviewed journal articles/conference proceedings as well as industrial white papers are reviewed. Harzing Publish or Perish software was employed to investigate and critically analyse the trends and perspectives of “big data” applications between 2010 and 2015.
The four main attributes or factors identified with “big data” include – big data development sources (Variety – V1), big data acquisition (Velocity – V2), big data storage (Volume – V3), and finally big data analysis (Veracity – V4). However, the study of “big data” has evolved and expanded a lot based on its application and implementation processes in specific industries in order to create value (Value-adding – V5) – “Big Data cloud computing perspective/Internet of Things (IoT)”. Hence, the four Vs of “big data” is now expanded into five Vs.
This paper presents original literature review research discussing “big data” issues, trends and perspectives in operations/supply-chain management in order to propose “Big data II” (IoT – Value-adding) framework. This proposed framework is supposed or assumed to be an extension of “big data” in a value-adding perspective, thus proposing that “big data” be explored thoroughly in order to enable industrial managers and businesses executives to make pre-informed strategic operational and management decisions for increased return-on-investment (ROI). It could also empower organizations with a value-adding stream of information to have a competitive edge over their competitors.
More than ever companies are challenged to rethink their offerings while simultaneously being provided with a unique opportunity for creating or recreating their product-service systems. This paper ...seeks to address how servitisation can utilise the third wave of Internet development, referred to as the Internet of Things (IoT), which may unlock the potential for innovative product-service systems on an unprecedented scale. By providing an analysis of this technological breakthrough and the literature on servitisation, these concepts are combined to address the question of how organisations offering product-service systems can reap the benefits that the IoT. An analysis of three successful IoT implementation cases in manufacturing companies, representing different industry sectors such as metal processing, power generation and distribution, is provided. The results of the empirical research presented in the paper provide an insight into different ways of creating value in servitisation. The paper also proposes a framework that is aimed at proving a better understanding of how companies can create value, and add it to their servitisation processes with, the data obtained by the IoT based solutions. From the value chain perspective, IoT aided servitisation enables organisations to extend their value chains in order better serve their customers which, in turn, might result in increased profitability. The article proposes further research avenues, and offers valuable insight for practitioners.
•Internet of Things can enable possibilities of servitization for manufacturing companies.•Three case examples are analysed from value chain perspective.•IoT provides opportunity to access end-user operations and build service-products on data analytics.•A desired value chain positioning shift is toward downstream.
•A system dynamics model for evaluating renewable energy policies on dependency is proposed.•The model considers the role of diversification on dependency and security of energy supply in ...Finland.•Dependency on imported sources will decrease depends on the defined scenarios in Finland.
We discuss the role of diversification on dependency and security of energy supply. A system dynamics model with especial focus on the role of renewable energy resources (as a portfolio) on Finland’s energy dependency is developed. The purpose is also to cover a part of research gap exists in the system dynamics modeling of energy security investigations.
A causal loops diagram and a system dynamics model evaluate Finnish scenarios of renewable energy policies. The analysis describes the relationship between dynamic factors such as RE encouragement packages, dependency, and energy demand.
A causal loops diagram and a system dynamics model evaluate three different Finnish scenarios of renewable energy policies by 2020.
Analysis shows that despite 7% electricity/heat consumption growth by 2020 in Finland, dependency on imported sources will decrease between 1% and 7% depend on the defined scenarios.
The proposed model not only helps decision makers to test their scenarios related to renewable energy polices, it can be implemented by other countries.
Extended producer responsibility (EPR) is commonly implemented as a strategy in waste management. The core of the concept itself is a waste reverse logistics (WRL), which dictates how the collection, ...inspection and processing of end-of-life products are performed. Existing studies of EPR mainly focused on single products instead of using broader perspective on national level. Its contribution towards circular economy through slowing and closing the loops also has not been widely discussed. This study examined the system architecture of the policy instruments used in the EPR and the similarities of the WRL networks across different products. A case study was used to investigate six products: portable batteries and accumulators, paper, packaging, vehicles, electrical and electronic equipment (EEE) and tyres. The study generated a WRL framework. It is also observed that closing the loop through recycling is the primary circular strategy and is found in all products, whereas closing and slowing the loop strategy through reuse/repair, remanufacture and repurposing is found in packaging, tyres, vehicles and EEE. This study shows that EPR can close the material loop, although improvement in design for the environment is necessary. It creates challenges and opportunities for the government, producer responsibility organization and producers to improve existing conditions by implementing new initiatives such as design for the environment indicators, standardization, tax and subsidy systems and tariffs for disposal fees.
This study develops a cost model covering monetary and environmental damage costs for source-separated biowaste collection. The model provides an improved basis for decision-making by including ...environmental damage costs compared to the assessment that considers the only monetary cost. The monetary cost calculation integrated route optimisation using existing road networks, while the environmental damage cost was estimated using the life cycle impact assessment method based on the endpoint (LIME) model. The model was tested in the Finnish case where the new law implements the stricter requirement for source-separated biowaste. The costs of collection, transportation and treatment of three different scenarios were assessed: mixed waste under the old law (MW-OL), biowaste under the new law (B-NL) and mixed waste without biowaste under the new law (MW-NL). The results showed the economic and environmental benefits of sourced separated biowaste. The overall cost of collection and transportation (CT) under the old law and new laws were 80.7 € Mg−1 and 81.1 € Mg−1, respectively. Treatment costs were 79 € Mg−1 and 64.8 € Mg−1 under the old and new laws, respectively. The damage costs for CT under the old and new laws were 0.23 € Mg−1 and 0.24 € Mg−1, respectively. At the same time, the damage costs from the treatment stage were 4.9 € Mg−1 and 3.5 € Mg−1 under the old law and new law, respectively. The model supports decision-making when the collection scheme requires a change. Failing to plan an optimised solution and cost will lead to inefficient systems.
Product family design by module configuration is conducive to accommodating product variety while maintaining mass production efficiency. Effective fulfillment of product families necessitates joint ...decision making of product family configuration (PFC) and downstream supply chain configuration (SCC), due to nowadays manufacturers’ moving towards assembly-to-order production throughout a distributed supply chain network. Existing decision models for joint optimization of product family and supply chain configuration are originated from an “all-in-one” approach that assumes both PFC and SCC decisions can be integrated into one optimization problem by aggregating two different types of objectives into a single objective function. Such an assumption neglects the complex tradeoffs underlying two different decision making problems and fails to reveal the inherent coupling of PFC and SCC.
This paper formulates joint configuration of a product family and its supply chain as a leader-follower Stackelberg game that is enacted through a bi-level hierarchical optimization mechanism to model the coordination between two self-interested decision makers for PFC and SCC. The PFC decisions are modeled as an upper-level optimization problem (called leader) for optimal selection of modules, module instances, and product variants. The SCC decisions are modeled as a lower-level optimization problem (called follower), which responds to decisions of the upper level in order to determine an optimal supply chain configuration and inventory policies. A nonlinear, mixed integer programming model is formulated for the bi-level joint decision in the leader-follower game. To solve the nonlinear optimization model, a bi-level, nested genetic algorithm with constraint reasoning is developed and implemented. A case study of a power transformer product family and supply chain configuration is reported to demonstrate the feasibility and potential of the proposed leader-follower game-theoretic method.
•Studies in joint configuration of product families and supply chains are reviewed.•Mathematical models for product families and supply chains are formulated.•Joint configuration is modeled by a Stackelberg game.•A bi-level, nested genetic algorithm is employed to solve the game.•Experiments are conducted and the managerial implications are discussed.
This paper aims to model and minimize transportation costs in collecting tree logs from several regions and delivering them to the nearest collection point. This paper presents agent-based modeling ...(ABM) that comprehensively encompasses the key elements of the pickup and delivery supply chain model and presents the units as autonomous agents communicating. The modeling combines components such as geographic information systems (GIS) routing, potential facility locations, random tree log pickup locations, fleet sizing, trip distance, and truck and train transportation. ABM models the entire pickup and delivery operation, and modeling outcomes are presented by time series charts such as the number of trucks in use, facilities inventory, and travel distance. In addition, various simulation scenarios are used to investigate potential facility locations and truck numbers and determine the optimal facility location and fleet size.
Deep Neural Networks (DNN’s) present some of the leading applications of Artificial Intelligence (AI) which have proven suitability on various machine-learning use cases. Forecasting demand of ...intermittent on-line sales is a task which needs to be carried out automatically for a large number of Stock Keeping Units (SKU’s). This paper discusses the intermittent online sales and proposes an AI-based model for forecasting demand. We provide empirical evidence by utilizing data from 17 different sellers with approximately 3000 orders in total. Our findings indicate that thanks to their multi-layered learning structure, the DNN’s can provide up to 35% better accuracy than the classic models such as Moving Average, Exponential Smoothing, Croston’s method and ARIMA. Also, it was revealed that the time between orders’ arrivals follow Exponential distribution and the order sizes also generally follow Exponential distribution. Thus, most of the time, Poisson Exponential distribution can be used for modelling intermittent sales process through online platforms. The analyses show that Poisson Exponential distribution can generate values close to real sales with less than 7% error margin with real data.
Managing project scope creep in construction industry Ajmal, Mian M.; Khan, Mehmood; Gunasekaran, Angappa ...
Engineering, construction, and architectural management,
08/2022, Letnik:
29, Številka:
7
Journal Article
Recenzirano
Odprti dostop
PurposeProject scope creep is a nightmare and nearly intolerable task. Most project managers struggle to curtail the expanse and degree of scope creep. This study examines different likely project ...scope creep factors associated with the construction industry projects.Design/methodology/approachAfter many brainstorming sessions with construction stakeholders, several project scope creep factors were identified. Then, a detailed survey was executed in big construction projects of the United Arab Emirates (UAE). The data were analyzed using exploratory factor analysis (EFA) and confirmatory factor analysis (CFA).FindingsThe results derived and validated five conspicuous factors leading to project scope creep. Respectively, the highest and the lowest impact on project scope appears to be imposed by tasks/specifications and complexity/uncertainty.Practical implicationsIt offers crucial support to the project stakeholders in scrutinizing different factors that stand as hurdles to project success and allows them to seek remedies to resolve them.Originality/valueIt is among the first study in the region that identifies and validates the factors that hinder construction project success.
Managing the production and operations of a contemporary electronics manufacturing is challenging. Companies need to be proactive for uncertainties of the market in a productive way. This paper ...analyses the electronics manufacturing context and proposes the data system implementations based on context requirements. The general trends in electronics manufacturing are time-based competition, increasing product variety and new technologies. Cost structure changes are driving productivity. Price erosion is forcing flexible operations and fast inventory turn rates. The uncertainties in electronics manufacturing that need especial management are: volume - the change in demand and its effect on lead-time of order-fulfilment; product mix - managing product variety and lot sizing issues and product life cycles - changing products and production technologies. Managing and measuring these dimensions require wide implementation of ERP packages. In some cases, more advance planning tools such as product configurators and advanced planning systems are required.
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