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Record W3197910768 · doi:10.1108/ecam-11-2020-0955

Integrating lean production strategies, virtual reality technique and building information modeling method for mass customization in cabinet manufacturing

2021· article· en· W3197910768 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEngineering Construction & Architectural Management · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicProduct Development and Customization
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMass customizationPersonalizationComputer scienceLean manufacturingProduction (economics)Manufacturing engineeringProcess managementInformation systemSystems engineeringKnowledge managementEngineering

Abstract

fetched live from OpenAlex

Purpose In response to increasing demand for a fully customized and individualized home environment, mass customization (MC) has been suggested as an effective strategy to fulfill the customer’s customization needs while keeping production cost-effectiveness. However, in current practice, the implementation of the MC in the industrialized housing industry has not achieved an ideal level. Little effort was devoted to customer value generation and achieving lean production in a multi-disciplinary MC environment. In this concern, a highly efficient and flexible production information system is expected to capture accurately the customer’s demand and efficiently perform work planning for encouraging customer involvement and mass efficiency production. Design/methodology/approach To gain an insight into the development of the MC production information system for the housing industry and to depict the interaction among system modules, this study used a design science research methodology for a case study of customized cabinet production information system development. Findings A prototype of the production information system was proposed in this paper, supported by three information technologies to facilitate the MC implementation in the millwork manufacturer. A focus group discussion method was carried out for evaluating the system feasibility and the subsequent survey analysis on the virtual reality (VR) interface experiment. The evaluation process results showed that the VR interface is an effective medium for design information communication and encourages customer involvement. Most participants believed that the proposed production information system could generally benefit the MC implementation and improve production efficiency. Originality/value This study integrated lean production principles along with building information modelling, VR and discrete-event simulation in the production information system to assist the manufacturer in effectively handling variant product information and enabling quicker reactions in response to diverse customer requirements in housing industries. The coordination among system modules and the managed information flow could be a valuable reference for future MC production system development in housing industries.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.602
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.216
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it