Antonio Casimiro Caputo, Pacifico Marcello Pelagagge and Paolo Salini
The purpose of this paper is to develop a quantitative model to assess probability of errors and errors correction costs in parts feeding systems for assembly lines.
Abstract
Purpose
The purpose of this paper is to develop a quantitative model to assess probability of errors and errors correction costs in parts feeding systems for assembly lines.
Design/methodology/approach
Event trees are adopted to model errors in the picking-handling-delivery-utilization of materials containers from the warehouse to assembly stations. Error probabilities and quality costs functions are developed to compare alternative feeding policies including kitting, line stocking and just-in-time delivery. A numerical case study is included.
Findings
This paper confirms with quantitative evidence the economic relevance of logistic errors (LEs) in parts feeding processes, a problem neglected in the existing literature. It also points out the most frequent or relevant error types and identifies specific corrective measures.
Research limitations/implications
While the model is general purpose, conclusions are specific to each applicative case and are not generalizable, and some modifications may be required to adapt it to specific industrial cases. When no experimental data are available, human error analysis should be used to estimate event probabilities based on underlying modes and causes of human error.
Practical implications
Production managers are given a quantitative decision tool to assess errors probability and errors correction costs in assembly lines parts feeding systems. This allows better comparing of alternative parts feeding policies and identifying corrective measures.
Originality/value
This is the first paper to develop quantitative models for estimating LEs and related quality cost, allowing a comparison between alternative parts feeding policies.
Details
Keywords
Antonio C. Caputo, Pacifico M. Pelagagge and Paolo Salini
– The purpose of this paper is to develop an optimization model allowing the choice of parts feeding policy to assembly lines in order to minimize total cost.
Abstract
Purpose
The purpose of this paper is to develop an optimization model allowing the choice of parts feeding policy to assembly lines in order to minimize total cost.
Design/methodology/approach
An integer linear programming mathematical model is developed to assign the optimal material feeding policy to each part type. The model allows choice between kitting, line stocking and just in time delivery policies.
Findings
The choice of assembly lines feeding policy is not trivial and requires a thorough economic comparison of alternatives. It is found that a proper mix of parts feeding policies may be better that adopting a single material delivery policy for all parts.
Research limitations/implications
The model is aimed at single-model assembly lines operating in a deterministic environment, but can be extended to the multi-model line case. While relevant quantitative cost drivers are included, some context-related qualitative factors are not included yet. The model assumes that information about product structure and part requirements are known and that a preliminary design of the assembly system has been carried out.
Practical implications
Production managers are given a quantitative-decision tool to determine the optimal mix of material supply policies at an early decision stage.
Originality/value
Respect previous simplified literature models, this approach allows to quantify a number of additional factors which are critical for successful implementation of cost-effective parts feeding systems, allowing comparison of alternative policies on a consistent basis.
Details
Keywords
Antonio C. Caputo, Pacifico M. Pelagagge and Paolo Salini
– The aim of this paper is to develop a detailed descriptive model for kitting operations, allowing resources sizing and computation of systems’ economic performances.
Abstract
Purpose
The aim of this paper is to develop a detailed descriptive model for kitting operations, allowing resources sizing and computation of systems’ economic performances.
Design/methodology/approach
A mathematical model allows to size resources, given product characteristics and production mix, and determines total system costs by assessing relevant cost items including investment costs (vehicles, containers, storage racks), direct operating costs (transport and kitting workforce, vehicles energy consumption and maintenance, quality costs), indirect operating costs (space requirements, work in process (WIP) and safety stock holding costs, administration and control).
Findings
The choice of parts delivery supply to assembly lines requires a thorough economic comparison of alternatives. However, existing models are often simplistic and neglect many critical factors which affect the systems’ performances. As a consequence, industries are unsure about which system is best for their environment. This model allows assessment of the cost and suitability of kitting in any specific industrial setting. Results of the model application are case-specific and cannot be generalized, but the major impact of labour and error correction cost has been highlighted.
Research limitations/implications
The model at present focusses on the in-house kitting systems based on travelling kits concept only. Although all quantitative cost drivers are included, some context-related qualitative decision factors are not yet included. The model assumes that the information about product structure and part requirements is known and that a preliminary design of the assembly system (i.e. line balancing) has been carried out.
Practical implications
Production managers are given a quantitative decision tool to properly assess the implementation of kitting policies at an early decision stage. This allows exploring the trade-offs between the alternatives and properly planning the adoption of kitting systems, as well as comparing kitting with alternative material supply methods.
Originality/value
With respect to previous simplified literature models, this new approach allows quantification of a number of additional factors which are critical for successful implementation of cost-effective kitting systems, including kitting errors. An exhaustive cost estimation of kitting systems in multiple, mixed-model assembly lines is thus permitted.
Details
Keywords
Antonio C. Caputo, Pacifico M. Pelagagge and Paolo Salini
The purpose of this paper is to develop analytical planning models to compare just-in-time (JIT) delivery and line storage (LS) alternatives for a continuous supply of materials…
Abstract
Purpose
The purpose of this paper is to develop analytical planning models to compare just-in-time (JIT) delivery and line storage (LS) alternatives for a continuous supply of materials to assembly lines.
Design/methodology/approach
A mathematical model is developed to size resources and to determine total system costs.
Findings
The choice of assembly lines feeding policy requires a thorough economic comparison of alternatives. However, the existing models are often simplistic, neglecting many critical factors which affect the systems’ performances. As a consequence, industries are unsure about which system is best for their environment. This model allows to compare the cost and suitability of two major continuous-supply alternatives in any specific industrial setting. Results of the model application are case-specific and cannot be generalized.
Research limitations/implications
The model is aimed at single-model assembly lines operating in a deterministic environment. Although relevant quantitative cost drivers are included, some context-related qualitative factors are not yet included. The model assumes that the information about product structure and part requirements is known and that a preliminary design of the assembly system has been carried out.
Practical implications
Production managers are given a quantitative decision tool to properly assess the implementation of continuous material supply policies at an early decision stage, and determine which option is the best, also allowing to explore trade-offs between the alternatives.
Originality/value
With respect to previous simplified literature models, this new approach allows to quantify a number of additional factors which are critical for the successful implementation of cost-effective continuous-supply systems, including error costs. No other direct comparison of LS and JIT is available in the literature.
Details
Keywords
Antonio C. Caputo, Pacifico M. Pelagagge and Paolo Salini
The purpose of this paper is to estimate delivered hydrogen cost including both transport and expected accidents cost comparing compressed gas or liquid hydrogen road transport…
Abstract
Purpose
The purpose of this paper is to estimate delivered hydrogen cost including both transport and expected accidents cost comparing compressed gas or liquid hydrogen road transport. The model allows to determine whether, in a given context, the risk of accidents is an influencing variable in the selection of the hydrogen transport mode. It also helps to select the lowest cost transport mode and route.
Design/methodology/approach
Transportation cost models are developed and integrated with a risk analysis model to determine expected accidents cost so that an overall delivered hydrogen cost can be computed. Alternative transport modes are compared on the basis of hydrogen demand, delivery distance and route type.
Findings
While safety cost in many cases can be considered negligible with respect to overall hydrogen transport cost, there are cases (high flow rate, long distance) where accident cost is relevant, especially in routes through densely populated areas. In such cases, factoring in accidents cost may significantly affect the break even point between CH2 and LH2 transport alternatives.
Research limitations/implications
The paper only deals with proven road transportation methods (CH2 and LH2). Inclusion of alternative transport modes such as pipeline or hydrides is a future research goal.
Practical implications
Decision makers can examine the costs implied by hydrogen transportation alternatives in different economic scenarios factoring in safety costs to make informed decision.
Originality/value
Available hydrogen transportation cost models neglect any safety issue, while risk assessment models only consider accident consequences costs. This work integrates both views.
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Vasco Boatto, Luca Rossetto, Paolo Bordignon, Rosa Arboretti and Luigi Salmaso
The purpose of this paper is to detect market segments where consumers have a different knowledge of domestic and imported Parmesan cheese in USA and Canada. The results may be…
Abstract
Purpose
The purpose of this paper is to detect market segments where consumers have a different knowledge of domestic and imported Parmesan cheese in USA and Canada. The results may be helpful in understanding to what extend North America consumers appreciate Parmesan cheese and brands, Parmesan consumption and price while recognizing market segments according to consumer awareness, involvement and covariate effects.
Design/methodology/approach
A class of mixture models, known as combination uniform binomial (CUB), is applied to survey data collected in USA and Canada. A questionnaire, filled out by 540 restaurant customers, collects opinions about consumption, purchase features and price. The CUB model estimates the two latent variables, known as feeling and uncertainty, explaining the respondent’s behavior as awareness and involvement variability while the CUB clustering procedure detects market segments.
Findings
CUB results show that the Parmesan is a well-known cheese but also that a small share of consumers look for the place of origin. The model detects market segments where consumers express better awareness on taste, price and origin while the knowledge of imported Parmesan brands is lacking. Most of consumers, not paying attention to the origin, would hardly switch to the imported Parmesan because of higher price or because they are already satisfied of the domestic cheese.
Research limitations/implications
The results suffer some restrictions in the sample representativeness. A further analysis, where the survey is done at retail and advances in CUB models, may improve the market segmentation procedure allowing a better generalization of results.
Practical implications
The survey results highlights the appreciation and consumption of Parmesan cheese, especially for its taste, as well as a low perception of Italian brands. Consequently, trade companies should focussed their communication strategy on activities encouraging North American consumers to taste Italian Parmesan brands (e.g. tasting sessions, price promotions) instead of costly and less effective advertising campaigns.
Social implications
Parmesan brand misunderstandings are often associated with market information asymmetry. The paper results show a market segmentation where purchases are mainly driven by Parmesan taste regardless of domestic or imported brands. Likely, the consumption of domestic Parmesan is well consolidated and it is not a consequence of brand information asymmetry.
Originality/value
The CUB model is an innovative and flexible no parametric approach for evaluating consumer behavior and for segmenting the market while dealing with complex problems of food knowledge.
Details
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Rosa Arboretti and Paolo Bordignon
Packaging features have been shown to be of great importance for the consumer final choice of fresh products (Silayoi and Speece, 2007). Packaging is an extrinsic attribute, which…
Abstract
Purpose
Packaging features have been shown to be of great importance for the consumer final choice of fresh products (Silayoi and Speece, 2007). Packaging is an extrinsic attribute, which consumers tend to rely on, when relevant intrinsic attributes of the product are not available. In the current literature, studies on the influences of packaging features on consumer preferences are mainly related to classical preference evaluation methods like conjoint analysis (CA). The purpose of this paper is to apply both CA and the less known combination of uniform discrete and shifted binomial distributions (CUB) models to food packaging evaluations.
Design/methodology/approach
Starting from a real case study in this field, along with CA, the author apply CUB models (Iannario and Piccolo, 2010) as a useful tool to evaluate preferences. CUB models can grasp some psychological characteristics of consumers related to the “feeling” toward packaging attributes and related to an inherently “uncertainty” that affects the consumers’ choices. Both psychological characteristics “feeling” and “uncertainty” can be linked to relevant subject’s information. At first we detect preferred packaging attributes of fresh food by means of CA, then we apply CUB models to some relevant attributes from the CA study.
Findings
Results show that attributes like packaging material and size/shape of packaging are the most important attributes and that biodegradable packaging, reclosable trays/bags and long “best by” date are also valuable features for consumers. The introduction of covariates showed that specific demographic characteristics are linked to both feeling and uncertainty.
Originality/value
The “data driven” segmentation results give to the integrated approach “CUB models and Conjoint Analysis” the most important added value.