constructs of the 4 questionnaires showed acceptable consistency(Cronb terjemahan - constructs of the 4 questionnaires showed acceptable consistency(Cronb Melayu Bagaimana mengatakan

constructs of the 4 questionnaires

constructs of the 4 questionnaires showed acceptable consistency
(Cronbach's alpha ¼ 0.615). Next, the non-parametric KruskaleWallis
(KW) test was used to assess statistical differences on
the sample means. The option for the KW test is justified by the fact
that the sample is small, and there is no certainty regarding normal
distribution of data. The KW test does not require a normal distribution
of the residuals as the analogous one-way ANOVA does
(Corder and Foreman, 2009). Tukey's test was used to point out the
sectors that are significantly different from the others. Questions
related to workstation, work organization and company constructs
reflected EDIs particular to each sector, do not enabling direct
comparison among them. Comparative results presented in this
article were therefore drawn based on EDIs from physical environment,
work content and discomfort/pain constructs that were
common to all four evaluated sectors. Managers and supervisors
were not interviewed and did not answer questionnaires, therefore
their opinions regarding work performed in the sectors as well as
the possible solutions for improvement were obtained through
dialogues and discussions held on many occasions during the
interview process.
Diagnosis was split into ergonomic and production data analysis.
Ergonomics diagnosis mainly comprised the analysis of work
carried out in the four evaluated sectors and an in depth analysis of
the problems raised in the appraisal stage. Two ergonomists performed
non-systematic observations during a two-week period to
understand the work in each sector and their interactions. Work
was videotaped, and the cycle times required to perform different
tasks were recorded during different times of the journey. This data
allowed a posteriori assessment of how work was performed, a
more detailed time/motion analysis, and a postural risk evaluation
based on the computerized OWAS (WinOwas) method (Kivi and
Matilla, 1991).
Analysis of production outcomes included: 1) one year of historical
data from customer orders, product costs, commercial and
technical information of products with highest impact on Company's
revenue that was obtained from the commercial department
e this data was useful to select the product models to be analyzed;
and 2) cycle times and lead times, which was used to evaluate
production outcomes before and after the intervention; 3) operation,
waiting and transportation times on different tasks were
measured from the first (wooden frame assembly) until the last
(product expedition) operation of five highly demanded sofa
models. Data mentioned in 2) and 3) were collected by two industrial
engineers at different times of the day during the first two
weeks of the diagnosis stage. Data collection focused on two
courses of action: (i) counting manufacturing parts on all workstations
related to sofa manufacturing (enabling a snapshot of
process material accumulation), and (ii) collecting a minimum
sample of 10 replications of all times required for process
manufacturing in each workstation. Work-in-progress (WIP) data
was collected by counting the number of units waiting for process
on each workstation; the number of delayed days was provided by
the company personnel responsible for monitoring productive
levels.
Based on diagnosis and worker proposals raised in the appraisal
stage (interviews) the experts' team developed alternative solutions
that focused on the design of the new work system, although
workstation and environmental solutions were also proposed. One
of the alternatives was selected for prototyping and testing after
discussions between the experts' team and two managers. Some
changes in the work system and workstations were carried out and
tested based on feedback from 11 volunteer workers involved in the
prototyping stage and from the analysis from the experts' team.
Afterwards, the new design was qualitatively validated by the same
eleven workers, two managers and experts' team.
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constructs of the 4 questionnaires showed acceptable consistency(Cronbach's alpha ¼ 0.615). Next, the non-parametric KruskaleWallis(KW) test was used to assess statistical differences onthe sample means. The option for the KW test is justified by the factthat the sample is small, and there is no certainty regarding normaldistribution of data. The KW test does not require a normal distributionof the residuals as the analogous one-way ANOVA does(Corder and Foreman, 2009). Tukey's test was used to point out thesectors that are significantly different from the others. Questionsrelated to workstation, work organization and company constructsreflected EDIs particular to each sector, do not enabling directcomparison among them. Comparative results presented in thisarticle were therefore drawn based on EDIs from physical environment,work content and discomfort/pain constructs that werecommon to all four evaluated sectors. Managers and supervisorswere not interviewed and did not answer questionnaires, thereforetheir opinions regarding work performed in the sectors as well asthe possible solutions for improvement were obtained throughdialogues and discussions held on many occasions during theinterview process.Diagnosis was split into ergonomic and production data analysis.Ergonomics diagnosis mainly comprised the analysis of workcarried out in the four evaluated sectors and an in depth analysis ofthe problems raised in the appraisal stage. Two ergonomists performednon-systematic observations during a two-week period tounderstand the work in each sector and their interactions. Workwas videotaped, and the cycle times required to perform differenttasks were recorded during different times of the journey. This dataallowed a posteriori assessment of how work was performed, amore detailed time/motion analysis, and a postural risk evaluationbased on the computerized OWAS (WinOwas) method (Kivi andMatilla, 1991).Analysis of production outcomes included: 1) one year of historicaldata from customer orders, product costs, commercial andtechnical information of products with highest impact on Company'srevenue that was obtained from the commercial departmente this data was useful to select the product models to be analyzed;and 2) cycle times and lead times, which was used to evaluateproduction outcomes before and after the intervention; 3) operation,waiting and transportation times on different tasks weremeasured from the first (wooden frame assembly) until the last(product expedition) operation of five highly demanded sofamodels. Data mentioned in 2) and 3) were collected by two industrialengineers at different times of the day during the first twoweeks of the diagnosis stage. Data collection focused on twocourses of action: (i) counting manufacturing parts on all workstationsrelated to sofa manufacturing (enabling a snapshot ofprocess material accumulation), and (ii) collecting a minimumsample of 10 replications of all times required for processmanufacturing in each workstation. Work-in-progress (WIP) datawas collected by counting the number of units waiting for processon each workstation; the number of delayed days was provided bythe company personnel responsible for monitoring productivelevels.Based on diagnosis and worker proposals raised in the appraisalstage (interviews) the experts' team developed alternative solutionsthat focused on the design of the new work system, althoughworkstation and environmental solutions were also proposed. Oneof the alternatives was selected for prototyping and testing afterdiscussions between the experts' team and two managers. Somechanges in the work system and workstations were carried out andtested based on feedback from 11 volunteer workers involved in theprototyping stage and from the analysis from the experts' team.Afterwards, the new design was qualitatively validated by the sameeleven workers, two managers and experts' team.
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membina satu daripada 4 soal selidik menunjukkan konsisten yang boleh diterima
(alpha Cronbach ¼ 0,615). Seterusnya, KruskaleWallis bukan parametrik
(KW) ujian telah digunakan untuk menilai perbezaan statistik
min sampel. Opsyen bagi ujian KW itu wajar oleh fakta
bahawa sampel adalah kecil, dan tidak ada kepastian mengenai normal
taburan data. Ujian KW tidak memerlukan taburan normal
daripada sisa sebagai analogi sehala ANOVA tidak
(Corder dan Foreman, 2009). Ujian Tukey telah digunakan untuk membantu sepanjang
sektor yang jauh berbeza dari yang lain. Soalan-soalan
yang berkaitan dengan stesen kerja, organisasi kerja dan membina syarikat
mencerminkan Edis khusus kepada setiap sektor, jangan halang langsung
perbandingan di antara mereka. Keputusan perbandingan dibentangkan dalam ini
artikel telah oleh itu dibuat berdasarkan Edis daripada persekitaran fizikal,
kandungan kerja dan membina ketidakselesaan / kesakitan yang adalah
biasa kepada semua empat sektor dinilai. Pengurus dan penyelia
tidak ditemuramah dan tidak menjawab soal selidik, oleh itu
pendapat mereka mengenai kerja yang dilakukan dalam sektor serta
kemungkinan penyelesaian untuk penambahbaikan telah diperolehi melalui
dialog dan perbincangan yang diadakan banyak kali semasa
proses temuduga.
Diagnosis telah berpecah kepada ergonomik dan analisis data pengeluaran.
diagnosis Ergonomik terutamanya terdiri daripada analisis kerja
dijalankan dalam empat sektor dinilai dan mendalam analisis
masalah yang dibangkitkan di peringkat penilaian. Dua ergonomists dilakukan
pemerhatian bukan sistematik dalam tempoh dua minggu untuk
memahami kerja untuk setiap sektor dan interaksi mereka. Kerja
telah dirakam, dan masa kitaran yang diperlukan untuk melaksanakan yang berbeza
tugas telah direkodkan semasa masa yang berlainan perjalanan. Data ini
dibenarkan penilaian posteriori bagaimana kerja dilakukan, satu
analisis masa / gerakan yang lebih terperinci, dan penilaian risiko postur
berdasarkan OWAS berkomputer (WinOwas) kaedah (Kivi dan
. Matilla, 1991)
Analisis hasil pengeluaran termasuk: 1) satu tahun sejarah
data dari pesanan pelanggan, kos produk, komersial dan
maklumat teknikal produk dengan kesan tertinggi di Syarikat
hasil yang diperolehi daripada jabatan komersial
e data ini adalah berguna untuk memilih model produk yang akan dianalisis;
dan 2) masa kitaran dan masa plumbum, yang telah digunakan untuk menilai
hasil pengeluaran sebelum dan selepas campur tangan; 3) operasi,
menunggu dan pengangkutan kali pada tugas-tugas yang berbeza telah
diukur dari pertama (pemasangan bingkai kayu) sehingga yang terakhir
produk ekspedisi) operasi (lima sofa sangat dituntut
model. Data yang disebut dalam 2) dan 3) telah dikumpulkan oleh dua industri
jurutera pada masa yang berlainan daripada sehari selama dua pertama
minggu peringkat diagnosis. Pengumpulan data memberi tumpuan kepada dua
kursus tindakan: (i) mengira bahagian pembuatan pada semua stesen kerja
yang berkaitan dengan pembuatan sofa (membolehkan gambar
pengumpulan bahan proses), dan (ii) mengumpul minimum
sampel 10 ulangan setiap masa diperlukan untuk proses
pembuatan di setiap stesen kerja. Kerja dalam pelaksanaan (WIP) data
dikumpulkan dengan mengira bilangan unit menunggu proses
pada setiap stesen kerja; bilangan hari kelewatan telah disediakan oleh
kakitangan syarikat yang bertanggungjawab untuk memantau produktif
peringkat.
Berdasarkan diagnosis dan pekerja cadangan yang dibangkitkan dalam penilaian
peringkat (temubual) pasukan pakar-pakar 'membangunkan penyelesaian alternatif
yang memberi tumpuan kepada reka bentuk sistem kerja yang baru, walaupun
penyelesaian stesen kerja dan alam sekitar telah juga dicadangkan. Salah
satu alternatif yang telah dipilih untuk prototaip dan ujian selepas
perbincangan antara pasukan pakar-pakar 'dan dua pengurus. Beberapa
perubahan dalam sistem kerja dan stesen kerja telah dijalankan dan
diuji berdasarkan maklum balas daripada 11 pekerja sukarelawan yang terlibat dalam
peringkat prototaip dan daripada analisis pasukan pakar-pakar '.
Selepas itu, reka bentuk baru telah kualitatif disahkan oleh yang sama
sebelas pekerja, dua pengurus dan pasukan pakar-pakar '.
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