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Presents a linear goal programming (LGP) model, which can be used to derive an optimal daily production schedule for JIT production systems. Also provides an explanation of how a detailed post‐optimal LGP analysis can enable a decision maker to examine the effects of production scheduling in a JIT “mixed‐model” production environment. To illustrate the informational efficacy of the proposed JIT‐based LGP model, presents an illustrative example.

This paper deals with estimation of risk and the risk preference function when producers face uncertainties in production (usually labeled as production risk) and output price. These uncertainties are modeled in the context of production theory where the objective of the producers is to maximize expected utility of normalized anticipated profit. Models are proposed to estimate risk preference of individual producers under (i) only production risk, (ii) only price risk, (iii) both production and price risks, (iv) production risk with technical inefficiency, (v) price risk with technical inefficiency, and (vi) both production and price risks with technical inefficiency. We discuss estimation of the production function, the output risk function, and the risk preference functions in some of these cases. Norwegian salmon farming data is used for an empirical application of some of the proposed models. We find that salmon farmers are, in general, risk averse. Labor is found to be risk decreasing while capital and feed are found to be risk increasing.

This study aimed to develop the integration of the multiperiod production-distribution model in a closed-loop supply chain involving carbon emission and traceability. The developed model was for agricultural food (agri-food) products, considering the reverse flow of food waste from the disposal center (composting center) to producers.

The results indicate that integrating the production and distribution model considering food waste recycling provides low carbon emissions in lower total costs. The sensitivity analysis also found that there are trade-offs between production and distribution rate and food waste levels on carbon emission and traceability.

This study focuses on the mathematical modeling of a multiperiod production-distribution formulation for a closed-loop supply chain.

The model of the agri-food closed-loop supply chain in this study that considers food recycling and carbon emissions would help stakeholders involved in the agri-food supply chain to reduce food waste and carbon emissions.

Second-generation biofuel is regarded as a sustainable alternatives to fossil energy in transportation where electricity is not feasible. The main purpose of this study is to analyze how large-scale second-generation biofuel based on wood may affect the competitiveness of more mature bioenergy technologies such as bioheat through competition in the biomass market. The impacts on forest industries are also included.

An economic model for the energy and forest sectors based on partial equilibrium modeling is used to quantify the impacts of four different locations of biofuel production in Norway.

The results show that there are regional variations in biomass price effects depending on local raw material availability and costs of transport and import. Technologies allowing for a larger variety of wood biomass qualities will face lower biomass prices than technologies using only one species as raw material, causing less reduction in the production of bioheat and forest industrial products. For Norway specifically, the paper concludes that even if there is a potential for both increased bioheat generation and large-scale biofuel production, the production of second-generation biofuels based on domestic wood resources will cause a 5-20 percent reduction in bioheat generation depending on the scale of biofuel production.

This study demonstrates how impacts on biomass markets from establishment of biofuel production vary quite substantially with location, production level and choice of feedstock. One main finding is the quite large biomass cost impact that is seen in the model runs when introducing large-scale biofuel production. Increased biomass costs reduce the profitability and this must be taken into account when establishing a biofuel installation.

The originality of the paper is the analyses of biofuel impacts with a detailed model for biomass supply as the bioenergy and forest sectors.

The librarian and researcher have to be able to uncover specific articles in their areas of interest. This Bibliography is designed to help. Volume IV, like Volume III, contains features to help the reader to retrieve relevant literature from MCB University Press' considerable output. Each entry within has been indexed according to author(s) and the Fifth Edition of the SCIMP/SCAMP Thesaurus. The latter thus provides a full subject index to facilitate rapid retrieval. Each article or book is assigned its own unique number and this is used in both the subject and author index. This Volume indexes 29 journals indicating the depth, coverage and expansion of MCB's portfolio.

The emergence of distributed manufacturing (DM) is examined as a new form of localised production, distinct from previous manifestations of multi-domestic and indigenous production.

Supply network (SN) configuration and infrastructural provisioning perspectives were used to examine the literature on established localised production models as well as DM. A multiple case study was then undertaken to describe and explore the DM model further. A maximum variation sampling procedure was used to select five exemplar cases.

Three main contributions emerge from this study. First, the research uniquely brings together two bodies of literature, namely SN configuration and infrastructure provisioning to explore the DM context. Second, the research applies these theoretical lenses to establish the distinctive nature of DM across seven dimensions of analysis. Third, emerging DM design rules are identified and compared with the more established models of localised production, drawing on both literature and DM case evidence.

This study provides a rich SN configuration and infrastructural provisioning view on DM leading to a set of design rules for DM adoption, thus supporting practitioners in their efforts to develop viable DM implementation plans.

The authors contribute to the intra- and inter-organisational requirements for the emerging DM context by providing new perspectives through the combined lenses of SN configuration and infrastructural provisioning approaches.

Some hierarchical approaches for production planning in a batch type manufacturing environment are described. In a single stage production system, three aggregation levels exist: types, families and items. The performance of a hierarchical system model is largely dependent on the methods of disaggregation at different levels. This paper reports on a study of hierarchical methods at the family disaggregation level and incorporates a simple modification to improve upon a heuristic proposed by Winters. Results indicate that even a very simple hierarchical planning approach can give a significant reduction in backorders in a production shop having severe capacity restriction.

The purpose of this paper is twofold. In view of the importance of process platform‐based production configuration (PPbPC) in sustaining product family production efficiency, it is to study the underlying logic for configuring production processes for a product family based on a process platform. Second, it is to apply the Petri nets (PNs) techniques to model PPbPC, in attempting to shed light on the underlying logic.

The authors first identify the fundamental issues in PPbPC, including variety handling, process variation accommodation, configuration at different abstraction levels, and constraint satisfaction. To accommodate the corresponding modelling difficulties, the authors develop a formalism of hierarchical colored timed PNs (HCTPNs) based on the principles of hierarchical PNs, timed PNs, and colored PNs. In the formalism, three types of nets together with a system of HCTPNs are defined to address the modelling of PPbPC.

Applying HCTPNs to vibration motors' case has revealed the logic of specifying complete production processes of final products at different levels of abstraction to achieve production configuration. The preliminary results also further demonstrate the feasibility of modelling PPbPC based on HCTPNs.

Traditional approaches to planning production processes for individual products may limit production performance improvement when companies need to timely produce a high variety of customized products. Systematic methods should be developed to plan production processes for product families so as to achieve production efficiency while utilizing the existing manufacturing resources.

By integrating the advantages of existing PN techniques, the HCTPNs formalism is developed to shed light on planning production processes for product families. The resulting production configuration model can facilitate practitioners to achieve production efficiency in producing large numbers of customized products.

This paper aims to propose a model of production management that integrates knowledge management, as a third dimension, to the production and work dimensions and to identify factors that promote a favorable context for knowledge sharing and results achievement in the production operations shop floor environment.

The model proposed is built from opportunities identified in the literature review.

The factors in the model integrate its three main components: knowledge management, production organization and work organization, providing a representation of the dynamics of the workplace and shop floor environment.

The proposed model and its factors allow managers to better understand and to improve the organization activities, because it integrates knowledge management with the production organization and work organization components of traditional models.

Literature acknowledges the role of knowledge as competitive advantage, but it is still dealt in an implicit way within the traditional models of production management. This paper proposes a model and factors that provide a favorable context for tacit knowledge sharing and results achievement in the production operations shop floor environment. The model explicitly integrates knowledge management with traditional models' components.

The purpose of this paper is to examine the impact of applying two classical controller strategies, including two proportional (P) controllers with two feedback loops and one proportional–integral–derivative (PID) controller with one feedback loop, on the order and inventory performance within a production-inventory control system.

The simulation experiments of the dynamics behaviour of the production-inventory control system are conducted using a model based on control theory techniques. The Laplace transformation of an Order–Up–To (OUT) model is obtained using a state-space approach, and then the state-space representation is used to design and simulate a controlled model. The simulations of each model with two control configurations are tested by subjecting the system to a random retail sales pattern. The performance of inventory level is quantified by using the Integral of Absolute Error (IAE), whereas the bullwhip effect is measured by using the Variance ratio (Var).

The simulation results show that one PID controller with one feedback loop outperforms two P controllers with two feedback loops at reducing the bullwhip effect and regulating the inventory level.

The production-inventory control system is broken down into three components, namely: the forecasting mechanism, controller strategy and production-inventory process. A state-space approach is adopted to design and simulate the different controller strategy.