This paper provides a review and introduction on agile manufacturing. Tactics of agile manufacturing are mapped into different production areas (eight-construct latent): manufacturing equipment and technology, processes technology and know-how, quality and productivity improvement, production planning and control, shop floor management, product design and development, supplier relationship management, and customer relationship management. The implementation level of agile manufacturing tactics is investigated in each area. A structural equation model is proposed. Hypotheses are formulated. Feedback from 456 firms is collected using five-point-Likert-scale questionnaire. Statistical analysis is carried out using IBM SPSS and AMOS. Multicollinearity, content validity, consistency, construct validity, ANOVA analysis, and relationships between agile components are tested. The results of this study prove that the agile manufacturing tactics have positive effect on the overall agility level. This conclusion can be used by manufacturing firms to manage challenges when trying to be agile.
Agile manufacturing (AM) is described as new tactics of manufacturing. It emerged after lean production (LP). It represents pattern shifts from mass production (MP). It originated from the 21st century manufacturing enterprise study that was conducted at Lehigh University in the early 1990s [
According to Groover [
The international CAM-I [
Agile companies tend to reveal the following agile principles: (1) rapid configuration of resources to meet dynamic change of market opportunities; (2) managerial personnel needs and knowledge should be distributed to all level of enterprise on trust base; (3) building business relationships to effectively enhance competitiveness; (4) considerable attention on innovation and entrepreneurship should be highly considered; (5) considerable attention on the value of solutions to customers' problems rather than on the product cost and price.
Important aspects and tactics of AM are mapped into different production areas as shown in Table
Mappings of AM tactics to eight impact areas.
Impact area | Identifier | Agile tactic | Identifier |
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(1) Manufacturing equipment and technology | MET | Group technology, cellular layouts, continuous flow | GTC |
Production process reengineering | PPR | ||
Flexible manufacturing system | FMS | ||
CNC and DNC | CNC | ||
Robotics and PLC’s | PLC | ||
CAD/CAM, CAPP, and CIM | CIM | ||
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(2) Processes technology |
PTK | Removal of waste methods | RWM |
Reconfigurable, and continuously changeable system | RCS | ||
Rapid machine setups and changeovers | RSC | ||
Standardized operating procedures | SOP | ||
Rapid prototyping, remote, and e-manufacturing | E-M | ||
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(3) Quality and productivity improvement and measures | QPIM | Fast identification of in-process defects | FID |
Strategic focus on long-term productivity performance | LPP | ||
Modular production facilities | MPF | ||
Fast production cycle times | FPT | ||
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(4) Production planning |
PPC | Effective information system | EIS |
Make-to-order strategy | MTO | ||
Decision making at functional knowledge levels | DMK | ||
Manufacturing resource planning | MRP | ||
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(5) Shop floor management | SFM | High flexibility approaches | HFS |
General purpose equipments | GPE | ||
Effective communication technology | ECT | ||
Removal of waste methods | RWM | ||
Make-to-lot size | MLT | ||
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(6) Product design and development | PDD | Quick introduction of new products | QIN |
Rapid changes to control software | RCC | ||
Rapid prototyping, remote, and e-manufacturing | E-M | ||
CAD/CAM, CAPP, and CIM | CIM | ||
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(7) Supplier relationship management | SRM | Effective communication technology | ECT |
Long-term supplier relationship | LTR | ||
Supplier evaluation and selection | SES | ||
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(8) Customer relationship management | CRM | Immediate and quick delivery | IQD |
Effective communication technology | ECT | ||
Make-to-order strategy | MTO | ||
Competitive unit cost | CUC | ||
Product customization | PCU |
LP and AM are complement to each other and should not be viewed as competitive. They are mutually supportive. On the other hand, LP and AM use different statements of principles. The emphasis in LP seems to be more on technical and operational issues, while emphasis in AM is on enterprise and people issues. AM is broader in scope and more applicable to the enterprise level. On the other hand, LP tries to smooth out the production schedule and reduce batch sizes [
AM uses flexible production technology to minimize disruptions due to design changes. By contrast, the philosophy behind AM is to embrace unpredictable changes. The capacity of an agile company to adapt to changes depends on its capabilities to minimize the time and the cost of setup and changeover, to reduce inventories of finished products, and to avoid other forms of waste. Table
Comparison of agile manufacturing and lean production.
Dimension | Lean production | Agile manufacturing |
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Principles | Eliminate source of waste |
Customer enrichment |
Production quantity | Enhancement of mass production | Break with mass production; emphasis on mass customization |
Production flexibility | Flexible production for product variety | Greater flexibility for customized products |
Emphasis | On technical, operational issues and management of human resources | On organizational and people issues |
Application l | To the factory level | To the enterprise level |
Area of management | Emphasis on supplier management | Formation of virtual enterprises |
Area of change | Relies on smooth production schedule | Attempts to be responsive to change |
Attempts to eliminate source of waste | Embrace unpredictable market change | |
Market life | Short | Short |
Order initiation | Produce to order | Produce to order |
Information content | High | High |
Customer relationship | Continuing relationship | Continuing relationship |
Pricing by customer value | Pricing by customer value |
The proposed agile manufacturing system (AMS) is assumed to involve eight-construct latent listed in Table
Constructed latent of agile manufacturing system.
No. | Constructed latent | Identifier | |
---|---|---|---|
Agile manufacturing system (AMS) | 1 | Manufacturing equipment and technology | MET |
2 | Processes technology and know-how | PTK | |
3 | Quality and productivity improvement and measures | QPIM | |
4 | Production planning and control | PPC | |
5 | Shop floor management | SFM | |
6 | Product design and development | PDD | |
7 | Supplier relationship management | SRM | |
8 | Customer relationship management | CRM |
The relations between the specific equipment configurations with visual control and group technology are developed by [ MET implementation has a significant, positive effect on the development of AMS. MET implementation has no effect on the development of AMS. MET implementation has a significant, positive effect on the development of PTK. MET implementation has no effect on the development of PTK. MET implementation has a significant, positive effect on the development of QPIM. MET implementation has no effect on the development of QPIM. MET implementation has a significant, positive effect on the development of SFM. MET implementation has no effect on the development of SFM. MET implementation has a significant, positive effect on the development of PDD. MET implementation has no effect on the development of PDD.
The elimination of waste can (1) simplify organizations processes [
Researchers on AM have established that flexibility is the foundation of AM. Flexibility is classified into machine flexibility, routing flexibility, product flexibility, manufacturing system flexibility, strategic flexibility, volume flexibility, and so forth, [
Quinn et al. [ PTK implementation has a significant, positive effect on the development of AMS. PTK implementation has no effect on the development of AMS. PTK implementation has a significant, positive effect on the development of QPIM. PTK implementation has no effect on the development of QPIM.
Hormozi [
Agile-based manufacturing organizations have higher productivity market shares [
AM involves fundamental change in an organization's approach to cycle-time reduction [ QPIM implementation has a significant, positive effect on the development of AMS. QPIM implementation has no effect on the development of AMS. QPIM implementation has a significant, positive effect on the development of SRM. QPIM implementation has no effect on the development of SRM. QPIM implementation has a significant, positive effect on the development of CRM. QPIM implementation has no effect on the development of CRM.
Production planning and control PPC plays an important role in the competitive environments. PPC responds immediately to achieve higher service level of performance, better resource utilization, and less material loss. Yan [
Gold and Thomas [
Petri [ PPC implementation has a significant, positive effect on the development of AMS. PPC implementation has no effect on the development of AMS. PPC implementation has a significant, positive effect on the development of SFM. PPC implementation has no effect on the development of SFM.
In 1995, shop floor control functional diagram was developed by Technologies Enabling Agile Manufacturing “TEAM” [ SFM implementation has a significant, positive effect on the development of AMS. SFM implementation has no effect on the development of AMS.
Andrew [ PPD implementation has a significant, positive effect on the development of AMS. PPD implementation has no effect on the development of AMS.
SRM practices create common frame of reference to enable effective communication between enterprises. In agile environments, relationships and communication between suppliers should be flexible and responsive [ SRM implementation has a significant, positive effect on the development of AMS. SRM implementation has no effect on the development of AMS.
Traditional ways of communication with customers include Internet, business to customer B2C, business to business B2B. The Internet offers several advantages such as reduction of ordering process cost, revenue flow increase because of credit cards payment, global access, and pricing flexibility. In-house inventory placement, inventory pooling, forward placement, vendor-managed inventories VMI, and continuous replenishment program CRP may be used to build an effective agile customer relationship model. Hence, the following hypothesis is proposed: : CRM implementation has a significant, positive effect on the development of AMS. : CRM implementation has no effect on the development of AMS.
The conceptual relationship model between the eight-construct latent considered in this study is shown in Figure
Summary of relationships between various-model latent.
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CRM implementation has a significant, positive effect on the development of AMS. |
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CRM implementation has no effect on the development of AMS. | |
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SRM implementation has a significant, positive effect on the development of AMS. |
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SRM implementation has no effect on the development of AMS. | |
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PPD implementation has a significant, positive effect on the development of AMS. |
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PPD implementation has no effect on the development of AMS. | |
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SFM implementation has a significant, positive effect on the development of AMS. |
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SFM implementation has no effect on the development of AMS. | |
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PPC implementation has a significant, positive effect on the development of SFM. |
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PPC implementation has no effect on the development of SFM. | |
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PPC implementation has a significant, positive effect on the development of AMS. |
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PPC implementation has no effect on the development of AMS. | |
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QPIM implementation has a significant, positive effect on the development of CRM. |
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QPIM implementation has no effect on the development of CRM. | |
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QPIM implementation has a significant, positive effect on the development of SRM. |
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QPIM implementation has no effect on the development of SRM. | |
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QPIM implementation has a significant, positive effect on the development of AMS. |
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QPIM implementation has no effect on the development of AMS. | |
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PTK implementation has a significant, positive effect on the development of QPIM. |
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PTK implementation has no effect on the development of QPIM. | |
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PTK implementation has a significant, positive effect on the development of AMS. |
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PTK implementation has no effect on the development of AMS. | |
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MET implementation has a significant, positive effect on the development of PDD. |
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MET implementation has no effect on the development of PDD. | |
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MET implementation has a significant, positive effect on the development of SFM. |
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MET implementation has no effect on the development of SFM. | |
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MET implementation has a significant, positive effect on the development of QPIM. |
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MET implementation has no effect on the development of QPIM. | |
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MET implementation has a significant, positive effect on the development of PTK. |
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MET implementation has no effect on the development of PTK. | |
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MET implementation has a significant, positive effect on the development of AMS. |
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MET implementation has no effect on the development of AMS. |
The proposed conceptual model and research hypotheses.
Eight different questionnaire drafts were developed. The preliminary questionnaires were pilot tested and reviewed by managers of several industrial companies, extensive literature review, and group of graduate students. This process continues until all questions in the eight questionnaires are unambiguous, appropriate, and acceptable to respondents. Every questionnaire is concerned with the implementation of one impact area. It consists of five-point Likert scale anchored at (1) “Poor”, (2) “Fair”, (3) “Good”, (4) “Very good”, and (5) “Excellent”.
Jordanian companies listed in Jordan chamber of commerce were screened according to whether they have a potential of implementing lean tools or not. Consequently, questionnaire packets were distributed to 500 services and manufacturing companies. 456 companies have responded to the questionnaire packets. Data were collected through production managers, quality engineers, consultants, and owners. Cronbach's alpha
Consistency and reliability of the model.
Model mean |
Model variance |
Cronbach’s alpha | Internal correlations | Agility index (AG%) | |
---|---|---|---|---|---|
Model | 3.003 | 0.008 | 0.830 | 0.011 | 60.1 |
Some statistics of model and correlation coefficients.
Area | Agile tactic | Tactic mean |
Tactic variance |
Area-tactic correlations | Model-tactic correlations | Tactic (AG%) | Model-area correlations | Area (AG%) |
---|---|---|---|---|---|---|---|---|
(1) MET | GTC | 2.999 | 0.115 | 0.516* | 0.517* | 59.9 | ||
PPR | 2.986 | 0.120 | 0.518* | 0.337* | 59.7 | |||
FMS | 3.001 | 0.117 | 0.446* | 0.300* | 60.1 | 0.517* | 60.1 | |
CNC | 3.000 | 0.106 | 0.497* | 0.381* | 60.0 | |||
PLC | 3.028 | 0.126 | 0.524* | 0.366* | 60.0 | |||
CIM | 3.020 | 0.123 | 0.502* | 0.380* | 60.0 | |||
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(2) PTK | RWM | 3.002 | 0.120 | 0.561* | 0.470* | 60.0 | ||
RCS | 3.009 | 0.114 | 0.354* | 0.493* | 60.1 | |||
RSC | 2.997 | 0.114 | 0.413* | 0.048 | 59.9 | 0.542* | 60.1 | |
SOP | 3.004 | 0.109 | 0.486* | 0.357* | 60.0 | |||
E-M | 3.005 | 0.113 | 0.546* | 0.463* | 60.1 | |||
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(3) QPIM | FID | 3.014 | 0.114 | 0.533* | 0.333* | 60.3 | ||
LPP | 3.002 | 0.106 | 0.386* | 0.394* | 60.0 | 0.520* | 59.9 | |
MPF | 3.004 | 0.114 | 0.577* | 0.428* | 60.0 | |||
FPT | 2.969 | 0.135 | 0.579* | 0.398* | 59.3 | |||
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(4) PPC | EIS | 3.015 | 0.123 | 0.232* | 0.155* | 60.3 | ||
MTO | 3.014 | 0.131 | 0.580* | 0.407* | 60.2 | 0.496* | 60.0 | |
DMK | 2.996 | 0.132 | 0.548* | 0.351* | 59.9 | |||
MRP | 3.016 | 0.120 | 0.526* | 0.497* | 60.3 | |||
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(5) SFM | HFS | 2.984 | 0.108 | 0.542* | 0.352* | 59.7 | ||
GPE | 2.982 | 0.101 | 0.513* | 0.366* | 59.6 | |||
ECT | 3.011 | 0.124 | 0.558* | 0.589* | 60.2 | 0.627* | 59.9 | |
RWM | 3.002 | 0.120 | 0.470* | 0.561* | 60.0 | |||
MLT | 2.998 | 0.107 | 0.556* | 0.371* | 60.0 | |||
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(6) PDD | QIN | 2.984 | 0.121 | 0.578* | 0.384* | 59.7 | ||
RCC | 3.007 | 0.125 | 0.569* | 0.377* | 60.2 | 0.543* | 60.1 | |
E-M | 3.005 | 0.113 | 0.560* | 0.463* | 60.1 | |||
CIM | 3.020 | 0.123 | 0.575* | 0.380* | 60.0 | |||
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(7) SRM | ECT | 3.011 | 0.124 | 0.689* | 0.589* | 60.2 | ||
LTR | 3.000 | 0.111 | 0.613* | 0.430* | 60.0 | 0.571* | 60.1 | |
SES | 3.000 | 0.117 | 0.632* | 0.396* | 60.0 | |||
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(8) CRM | IQD | 3.016 | 0.122 | 0.556* | 0.351* | 60.3 | ||
ECT | 3.011 | 0.124 | 0.485* | 0.589* | 60.2 | |||
MTO | 3.014 | 0.131 | 0.505* | 0.407* | 60.2 | 0.633* | 60.2 | |
CUC | 2.997 | 0.119 | 0.515* | 0.355* | 59.9 | |||
PCU | 3.006 | 0.114 | 0.492* | 0.337* | 60.1 |
Tactic-tactic correlations at two-tailed significance level less than or equal to 0.05.
Independent tactic | Dependent tactic | |||||||||||||
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MLT | MTO | EIS | MBF | FID | RSC | RCS | RWM | CIM | PLC | CNC | FMS | PPR | GTC | |
PPR | No | |||||||||||||
CNC | No | |||||||||||||
PLC | No | |||||||||||||
CIM | No | |||||||||||||
RSC | No | No | No | No | No | No | No | No | ||||||
SOP |
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No | ||||||||||||
EM | No | |||||||||||||
FID | No | |||||||||||||
LPP | No | No | ||||||||||||
MBF | No | |||||||||||||
FPT | No | No | No | No | ||||||||||
EIS | No | No | No | |||||||||||
MTO | No | No | No | No | ||||||||||
DMK | No | |||||||||||||
MRP | No | No | ||||||||||||
HFS | No | |||||||||||||
GPE | No | No | ||||||||||||
ECT | No | No | No | |||||||||||
MLT | No | No | ||||||||||||
QIN | No | No | No | |||||||||||
RCC | No | No | No | |||||||||||
LTR | No | |||||||||||||
SES | No | No | No | |||||||||||
IQD | No | No | No | |||||||||||
CUC | No | No | No | |||||||||||
PCU | No | No |
No: Signifies no tactic-tactic correlation; otherwise there is a tactic-tactic correlation.
Interrelations between production areas are computed and investigated using correlation coefficients (see Table
Correlation matrix and fit indices for each production area.
Area-area correlation coefficients | Production area | Fit indices | ||||||||||||
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CRM | SRM | PDD | SFM | PPC | QPIM | PTK | MET | GFI | RMSEA |
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Chi ratio | DF |
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0.150** | 0.135** | 0.355** | 0.209** | 0.192** | 0.173** | 0.195** | 1 | MET | 0.91 | 0.023 | 0.00 | 2.69 | 90 | 242.1 |
0.213** | 0.161** | 0.328** | 0.348** | 0.106* | 0.128** | 1 | PTK | 0.70 | 0.024 | 0.00 | 2.72 | 65 | 177.1 | |
0.262** | 0.179** | 0.131** | 0.215** | 0.202** | 1 | QPIM | 0.96 | 0.026 | 0.00 | 2.95 | 189 | 558.9 | ||
0.320** |
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0.153** | 0.192** | 1 | PPC | 0.87 | 0.072 | 0.00 | 3.21 | 189 | 606.3 | |||
0.350** | 0.386** | 0.130** | 1 | SFM | 0.93 | 0.032 | 0.00 | 3.75 | 324 | 1215.6 | ||||
0.200** | 0.119* | 1 | PDD | 0.99 | 0.071 | 0.00 | 3.66 | 299 | 1095.4 | |||||
0.352** | 1 | SRM | 0.97 | 0.010 | 0.00 | 2.97 | 90 | 267.1 | ||||||
1 | CRM | 0.94 | 0.017 | 0.00 | 1.76 | 90 | 158.6 |
Table
Hypothesis testing results.
Alternative hypothesis | Internal correlation | Paired samples test |
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Decision | |||
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Area-area | Pearson |
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DF |
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CRM-AMS | 0.633 | 1.061 | 458 | 0.289 | 0.000 | Reject |
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SRM-AMS | 0.571 | 0.382 | 458 | 0.702 | 0.000 | Reject |
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PPD-AMS | 0.543 | 0.216 | 458 | 0.829 | 0.000 | Reject |
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SFM-AMS | 0.627 | −1.413 | 458 | 0.158 | 0.000 | Reject |
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PPC-SFM | 0.192 | 0.795 | 458 | 0.427 | 0.000 | Reject |
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PPC-AMS | 0.496 | −0.034 | 458 | 0.973 | 0.000 | Reject |
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QPIM-CRM | 0.262 | −1.296 | 458 | 0.196 | 0.000 | Reject |
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QPIM-SRM | 0.179 | −0.809 | 458 | 0.419 | 0.000 | Reject |
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QPIM-AMS | 0.520 | −0.892 | 458 | 0.373 | 0.000 | Reject |
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PTK-QPIM | 0.128 | 0.661 | 458 | 0.509 | 0.006 | Reject |
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PTK-AMS | 0.542 | 0.093 | 458 | 0.926 | 0.000 | Reject |
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MET-PDD | 0.355 | 0.226 | 458 | 0.821 | 0.000 | Reject |
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MET-SFM | 0.209 | 1.297 | 458 | 0.195 | 0.000 | Reject |
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MET-QPIM | 0.173 | 1.001 | 458 | 0.317 | 0.000 | Reject |
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MET-PTK | 0.195 | 0.322 | 458 | 0.748 | 0.000 | Reject |
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MET-AMS | 0.517 | 0.590 | 458 | 0.556 | 0.000 | Reject |
One-way ANOVA analysis.
Area | Factor | Sum of squares | DF |
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Mean square |
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Conclusion | |
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Between groups | 27.295 | 155 | 0.176 | |||||||
GTC | Within groups | 25.452 | 303 | 155 | 303 | 2.096 | 0.000 | GTC has an effect on MET. | ||
Total | 52.746 | 458 | 0.084 | |||||||
Between groups | 25.946 | 155 | 0.167 | |||||||
PPR | Within groups | 29.188 | 303 | 155 | 303 | 1.738 | 0.000 | PPR has an effect on MET. | ||
Total | 55.134 | 458 | 0.096 | |||||||
Between groups | 25.500 | 155 | 0.165 | |||||||
FMS | Within groups | 28.107 | 303 | 155 | 303 | 1.774 | 0.000 | FMS has an effect on MET. | ||
MET | Total | 53.607 | 458 | 0.093 | ||||||
Between groups | 24.156 | 155 | 0.156 | |||||||
CNC | Within groups | 24.279 | 303 | 155 | 303 | 1.945 | 0.000 | CNC has an effect on MET. | ||
Total | 48.435 | 458 | 0.080 | |||||||
Between groups | 30.639 | 155 | 4.801 | |||||||
PLC | Within groups | 27.174 | 303 | 155 | 303 | 2.204 | 0.000 | PLC has an effect on MET. | ||
Total | 57.813 | 458 | 0.008 | |||||||
Between groups | 30.141 | 155 | 0.194 | |||||||
CIM | Within groups | 26.075 | 303 | 155 | 303 | 2.260 | 0.000 | CIM has an effect on MET. | ||
Total | 56.215 | 458 | 0.086 | |||||||
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Between groups | 30.796 | 142 | 0.217 | |||||||
RWM | Within groups | 24.046 | 316 | 142 | 316 | 2.850 | 0.000 | RWM has an effect on PTK. | ||
Total | 54.842 | 458 | 0.076 | |||||||
Between groups | 27.640 | 142 | 0.195 | |||||||
RCS | Within groups | 24.490 | 316 | 142 | 316 | 2.512 | 0.000 | RCS has an effect on PTK. | ||
Total | 52.130 | 458 | 0.077 | |||||||
PTK | Between groups | 28.902 | 142 | 0.205 | ||||||
RSC | Within groups | 23.400 | 316 | 142 | 316 | 2.768 | 0.000 | RSC has an effect on PTK. | ||
Total | 52.302 | 457 | 0.074 | |||||||
Between groups | 25.482 | 142 | 0.179 | |||||||
SOP | Within groups | 24.349 | 316 | 142 | 316 | 2.329 | 0.000 | SOP has an effect on PTK. | ||
Total | 49.831 | 458 | 0.077 | |||||||
Between groups | 28.788 | 142 | 0.203 | |||||||
E-M | Within groups | 22.766 | 316 | 142 | 316 | 2.814 | 0.000 | E-M has an effect on PTK. | ||
Total | 51.554 | 458 | 0.072 | |||||||
Between groups | 27.024 | 123 | 0.220 | |||||||
FID | Within groups | 25.256 | 335 | 123 | 335 | 2.914 | 0.000 | FID has an effect on QPIM. | ||
Total | 52.280 | 458 | 0.075 | |||||||
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Between groups | 25.765 | 123 | 0.209 | |||||||
LPP | Within groups | 22.905 | 335 | 123 | 335 | 3.064 | 0.000 | LPP has an effect on QPIM. | ||
QPIM | Total | 48.670 | 458 | 0.068 | ||||||
Between groups | 27.214 | 123 | 0.221 | |||||||
MBF | Within Groups | 25.076 | 335 | 123 | 335 | 2.956 | 0.000 | MBF has an effect on QPIM. | ||
Total | 52.290 | 458 | 0.075 | |||||||
Between groups | 30.022 | 123 | 0.244 | |||||||
FPT | Within groups | 31.739 | 335 | 123 | 335 | 2.576 | 0.000 | FPT has an effect on QPIM. | ||
Total | 61.761 | 458 | 0.095 | |||||||
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Between groups | 14.408 | 63 | 0.229 | |||||||
EIS | Within groups | 42.077 | 395 | 63 | 395 | 2.147 | 0.000 | EIS has an effect on PPC. | ||
Total | 56.484 | 458 | 0.107 | |||||||
Between groups | 27.184 | 63 | 0.431 | |||||||
MTO | Within groups | 33.016 | 395 | 63 | 395 | 5.162 | 0.000 | MTO has an effect on PPC. | ||
PPC | Total | 60.200 | 458 | 0.084 | ||||||
Between groups | 25.489 | 63 | 0.405 | |||||||
DMK | Within groups | 34.816 | 395 | 63 | 395 | 4.590 | 0.000 | DMK has an effect on PPC. | ||
Total | 60.305 | 458 | 0.088 | |||||||
Between groups | 22.479 | 63 | 0.357 | |||||||
MRP | Within groups | 32.326 | 395 | 63 | 395 | 4.360 | 0.000 | MRP has an effect on PPC. | ||
Total | 54.805 | 458 | 0.082 | |||||||
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Between groups | 28.842 | 157 | 0.184 | |||||||
HFS | Within groups | 20.503 | 301 | 157 | 301 | 2.697 | 0.000 | HFS has an effect on SFM. | ||
Total | 49.345 | 458 | 0.068 | |||||||
Between groups | 25.126 | 157 | 0.160 | |||||||
GPE | Within groups | 21.336 | 301 | 157 | 301 | 2.258 | 0.000 | GPE has an effect on SFM. | ||
Total | 46.462 | 458 | 0.071 | |||||||
SFM | Between groups | 30.429 | 157 | 0.194 | ||||||
ECT | Within groups | 26.146 | 301 | 157 | 301 | 2.231 | 0.000 | ECT has an effect on SFM. | ||
Total | 56.575 | 458 | 0.087 | |||||||
Between groups | 32.023 | 157 | 0.204 | |||||||
RWM | Within Groups | 22.819 | 301 | 157 | 301 | 2.690 | 0.000 | RWM has an effect on SFM. | ||
Total | 54.842 | 458 | 0.076 | |||||||
Between groups | 28.198 | 157 | 0.180 | |||||||
MLT | Within groups | 20.592 | 301 | 157 | 301 | 2.625 | 0.000 | MLT has an effect on SFM. | ||
Total | 48.790 | 458 | 0.068 | |||||||
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Between groups | 32.806 | 198 | 0.166 | |||||||
QIN | Within groups | 22.685 | 260 | 198 | 260 | 1.899 | 0.000 | QIN has an effect on PDD. | ||
Total | 55.491 | 458 | 0.087 | |||||||
Between groups | 34.958 | 198 | 0.177 | |||||||
RCC | Within groups | 22.088 | 260 | 198 | 260 | 2.078 | 0.000 | RCC has an effect on PDD. | ||
PDD | Total | 57.046 | 458 | 0.085 | ||||||
Between groups | 31.232 | 198 | 0.158 | |||||||
E-M | Within groups | 20.322 | 260 | 198 | 260 | 2.018 | 0.000 | E-M has an effect on PDD. | ||
Total | 51.554 | 458 | 0.078 | |||||||
Between groups | 35.112 | 198 | 0.177 | |||||||
CIM | Within groups | 21.103 | 260 | 198 | 260 | 2.185 | 0.000 | CIM has an effect on PDD. | ||
Total | 56.215 | 458 | 0.081 | |||||||
| ||||||||||
Between groups | 32.171 | 57 | 0.564 | |||||||
ECT | Within groups | 24.404 | 401 | 57 | 401 | 9.274 | 0.000 | ECT has an effect on SRM. | ||
Total | 56.575 | 458 | 0.061 | |||||||
Between groups | 25.975 | 57 | 0.456 | |||||||
SRM | LTR | Within groups | 24.947 | 401 | 57 | 401 | 7.325 | 0.000 | LTR has an effect on SRM. | |
Total | 50.922 | 458 | 0.062 | |||||||
Between groups | 27.583 | 57 | 0.484 | |||||||
SES | Within groups | 25.817 | 401 | 57 | 401 | 7.516 | 0.000 | SES has an effect on SRM. | ||
Total | 53.400 | 458 | 0.064 | |||||||
| ||||||||||
Between groups | 23.490 | 67 | 0.351 | |||||||
IQD | Within groups | 32.175 | 391 | 67 | 391 | 4.260 | 0.000 | IQD has an effect on CRM. | ||
Total | 55.665 | 458 | .0082 | |||||||
Between groups | 19.922 | 67 | 0.297 | |||||||
ECT | Within groups | 36.653 | 391 | 67 | 391 | 3.172 | 0.000 | ECT has an effect on CRM. | ||
Total | 56.575 | 458 | 0.094 | |||||||
Between groups | 23.125 | 67 | 0.345 | |||||||
MTO | Within groups | 37.075 | 391 | 67 | 391 | 3.640 | 0.000 | MTO has an effect on CRM. | ||
CRM | Total | 60.200 | 458 | 0.095 | ||||||
Between groups | 21.242 | 67 | 0.317 | |||||||
CUC | Within groups | 33.350 | 391 | 67 | 391 | 3.717 | 0.000 | CUC has an effect on CRM. | ||
Total | 54.592 | 458 | .0085 | |||||||
Between groups | 19.211 | 67 | 0.287 | |||||||
PCU | Within groups | 33.062 | 391 | 67 | 391 | 3.391 | 0.000 | PCU has an effect on CRM. | ||
Total | 52.273 | 458 | 0.085 | |||||||
| ||||||||||
Between groups | 9.056 | 456 | 0.020 | |||||||
MET | Within groups | 0.043 | 2 | 456 | 2 | 0.928 | 0.659 | MET and AG have equal agility index. | ||
Total | 9.099 | 458 | 0.021 | |||||||
Between groups | 10.625 | 456 | 0.023 | |||||||
PTK | Within groups | 0.021 | 2 | 456 | 2 | 2.249 | 0.359 | PTK and AG have equal agility index. | ||
Total | 10.646 | 458 | 0.010 | |||||||
Between groups | 12.952 | 456 | 0.028 | |||||||
QPIM | Within groups | 0.113 | 2 | 456 | 2 | 0.501 | 0.863 | QPIM and AG have equal agility index. | ||
AG | Total | 13.066 | 458 | 0.057 | ||||||
Between groups | 12.912 | 456 | 0.028 | |||||||
PPC | Within groups | 0.037 | 2 | 456 | 2 | 1.539 | 0.477 | PPC and AG have equal agility index. | ||
Total | 12.949 | 458 | 0.018 | |||||||
Between groups | 10.510 | 456 | 0.023 | |||||||
SFM | Within groups | 0.033 | 2 | 456 | 2 | 1.411 | 0.507 | SFM and AG have equal agility index. | ||
Total | 10.543 | 458 | 0.016 | |||||||
Between groups | 13.612 | 456 | 0.030 | |||||||
PDD | Within groups | 0.006 | 2 | 456 | 2 | 10.509 | 0.091 | PDD and AG have equal agility index. | ||
Total | 13.618 | 458 | 0.003 | |||||||
Between groups | 18.103 | 456 | 0.040 | |||||||
SRM | Within groups | 0.036 | 2 | 456 | 2 | 2.233 | 0.361 | SRM and AG have equal agility index. | ||
Total | 18.139 | 458 | 0.018 | |||||||
Between groups | 10.186 | 456 | 0.022 | |||||||
CRM | Within groups | 0.002 | 2 | 456 | 2 | 29.566 | 0.033 | CRM and AG have equal agility index. | ||
Total | 10.188 | 458 | 0.001 |
This paper investigates the causal relationship model among implementation of thirty-six different agile tactics. These tactics are categorized into eight impact areas (manufacturing equipment and technology MET, processes technology and know-how PTK, quality and productivity improvement and measures QPIM, production planning and control PPC, Shop Floor Management SFM, product design and development PDD, supplier relationship management SRM, and customer relationship management CRM). Analysis of data is carried out using AMOS 19 and IBM SPSS 20 for Windows. The obtained results show strongly that the model is valid. The AMOS 19 software is used to test the model fit for each impact area. The results show that the model fit is good. All items loaded significantly on their corresponding constructs at the 0.05 level. This demonstrates a good model fit. The fit statistics indicate that the hypothesized structural model achieves an acceptable fit such that no further interpretation is required. The testing of the entire hypotheses shows that all impact areas have positive effect on AMS.
It was found out that the overall assumed agility index is about 60%, the average agility index of impact areas is about 60%, and the average agility index of agile tactics is about 60%. The correlation analyses show that all model constructs have a positive correlation with overall AMS model.
Estimates of the relations in the AMS are investigated and summarized as shown in Figure
Estimates of the relations between models constructs.
The implementation of agile manufacturing principles and tools in Jordanian firms is investigated. Different agile practices that are adopted by the considered firms to manage their AMS systems are identified based on empirical basis. This paper concludes that the existence of 36 different agile approaches can be adopted by the different firms to enhance their competitiveness. These approaches categorized into eight impact areas, namely, MET, PTK, QPIM, PPC, SFM, PDD, SRM, and CRM. The primary contribution of this paper is successfully analyzing the causal relationship of implementation level of agile production areas and their effect on the AMS using SME methodology. The results ensure that SEM is the correct method for investigating the relationship model between the eight-constructs considered in this study. IBM SPSS 20 and AMOS 19.0.0 software enable SEM to provide a clear and complete specification of the AMS and its constructs. The results of this study show that the studied agile tactics have significant relationship and are affected positively by the AMS. The implementation of each agile tactic contributes significantly to the performance of AMS. The approach presented in this study can be used to facilitate the implementation of agile practices in industries and measure correlation between them. It may be worthwhile to focus future research on modeling the implementation of lean production practices, such as kanban, just in time (JIT), pull production control strategy, and so forth, [
The authors are thankful to the anonymous referees for their valuable comments and suggestions which improved the presentation of the paper.