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Directions in Production Engineering Research – Part IV

The concluding Part IV of this series attempts to connect capability and ambitions of next-gen manufacturing to next high of interconnected processes and enterprises engulfed through a systems approach, where connectivity of resources will be provided industry wide through internet. Call this as Industrial Internet of Things, which will be governed over the cloud using secure and public or private domains allowing control over distances for effectiveness, efficiency and sustainability.

This part attempts to model the paradigm of manufacturing in internet 4.0 era for which the essence is in system thinking, and the end objective a competitive strength at sustainability, quality and cost. The cloud manufacturing provides a complete transparency, maneuverability and control at high speeds and over long distances, and needs to manage advanced processes, materials and technologies. The essence is in managing zero-defect zero-effect as a Make in India paradigm.


Research is an all-essential operator of the creative technological development. In Part I through III of this series, we had discussed how the technology had transformed from a state of ‘what’ and ‘how’ (in mode 1) to beyond ‘why’ and ‘how much,’ and where we are now going, duly interspersed in the systematic integration-disintegration of technology phases. Due to multiplexing of technology triangulated with tools and techniques, and teams explored in their various forms and kinds makes the possible research directions more elaborate. Thus maintaining a parallelism of R&D versus innovation, the agenda with a five-step roadmap was slowly charted, necessary for graduation to world class and fit for world markets. In the meantime, the erstwhile production maturity of the style of Mode 2 integration with more of IT (information technology) and a superior knowledge infrastructure involving cyber physical systems displayed the onset of a newer fourth phase of industrialization, also called Industry 4.0 era. This paradigm is set to enter now into the second-growth phase in the four-part life cycle phenomenon with well known steps of initiation, growth, maturity and decline.

Albeit, the scenario is complicated; being in a glocal (global+local) domain as modelled in Part II, it encompassed a new knowledge infrastructure which is prompted by ambition and limited by capability. Thus it was emphasized that for want of realization of ambition and capability, enhancement of production research needs be pursued at a pace of {economy × competence}. In other words, due investment into production engineering research that assures a pay back through increase in overall productivity and competence, is maintained. Increasingly, manufacturers are partnering with research institutions, suppliers and end-users to make better and better ‘smart devices’ communicating through an array of sensors. On an organized front, several research projects have been funded, viz., by the European 7th Framework Program (FP7) to investigate important research issues. However, there are many challenges, both at the level of technology and research initiatives. Regarding the lacunae at the latter, Jukes and McCain foresee the operators as similar to that of a quarterback on a football team, who “…must be a futurist-throwing the ball not to where the receiver is, but to where the receiver is going to be. It is much the same with technology.”

This is in line when viewed from the angle of value-chain perspective [6] which guides as to how a process is planned for future state performance. Pertaining to the trends in global manufacturing, Rodrigue et al. clarify that future developments in global manufacturing will be complemented by the enhancement of capabilities related to innovation, labor and infrastructures. On a similar note, Indian Prime Minister, Narendra Modi, proposed a concerted Make in India initiative, with the slogan Zero-Defect Zero-Effect coined by India that calls for setting up production mechanisms wherein processes and products have no defects and the process through which product with zero adverse environmental and ecological effects are produced. Both deem to be founded on a country’s production research and competence.

The Postulation of Industry 4.0 Era’s from a Current Grounding

In the present Part IV, I begin by identifying the operational paradigms latent from the works of various contributors, suggestive so as to succeed the Industry 4.0 era, and by stipulating their strategic vision for a future state, and chart a roadmap for research accomplishments. The collated analysis of this exercise should point toward the understanding of competencies (Wesselink et al., who call them comparable constructs) for sustaining a growth phase into future manufacturing. or Wu feels any comparison of the strategic vision and current state leads to discovery of relevant suggestions for future work.

The identification is attempted using Joiner’s triangulation again which calls for innovations in manufacturing competence, a culture and the system’s thinking toward sustainability for meeting of customer needs at one end, and new wetware technologies in the other-Tools and Technique’s segment. More tools include cloud manufacturing applications that enable flexibility with high speed over longer distances (HSLD) in processes and industrial control systems. The third apex of triad is facilitated by, say, innovations in manufacturing that provide for tomorrow’s manufacturing for various competencies and comparable constructs. These futuristic requirements are disparate but yet connected as in the Joiner system, as shown in Fig. 1.

Figure 1.The Constructs for Future Manufacturing Denoting Disparate Directions of Action and Innovation

Figure 1.The Constructs for Future Manufacturing Denoting Disparate Directions of Action and Innovation

I seek this view of collated competencies, which has broadened in requirements, to reach and accomplish over the years to the present levels after having interfaced with plethora of scientific advancements as a part of current technological revolution. This evolution has been systemic in nature, with innovations as input and total sustainability as the objective. Thus the flow of this article is also guided by sustainability requirements for maximizing the achievement to ambitious levels in new industry 4.0 era.

While one chases such an ambition, further analysis of duly charted capabilities attained as in Fig. 1 may be made for ascertaining current directions of production research. Thus, for demonstrating a system view, I split Fig. 1 into three sets of triple constructs and centered it by agile (concurrent and outcome-oriented) duly linking from current manufacturing abilities through the ambitions deserved from Industry 4.0 paradigm. The split modeling of the constructs depicts a structure where each and every apex is governed by a systemic approach as one adores in the exemplar in Fig. 2 listed schematically at the top apex of each set. For example, the step of Systems Thinking in the middle (top) as a process connects Innovations & action as an input (on the left) to finish on other side with Competent sustainability as output on the right. This is made to presents the like of an input -> process -> output (IPO system), which form as reprimanded from previous data as in Fig. 2.

Figure 2.The Constructs for Future Manufacturing from Fig. 1 Duly Split into Input-Process-Output

Figure 2.The Constructs for Future Manufacturing from Fig. 1 Duly Split into Input-Process-Output

The operators connected in them are guided by manufacturing capability at input, with a goal of expediting response time to market changes (call it agile manufacturing), to achieve the Industry 4.0 ambition.

This is how manufacturing was defined by McKinsey & Company: “The new era of manufacturing will be marked by highly agile, networked enterprises that use information and analytics as skillfully as they employ talent and machinery to deliver products and services to diverse global markets.” McKinsey uses a requirement ‘Agile’ which gets defined as “one engaged in high-volume, made-to order, arbitrary-lot-size production enabled by an information technology intensive flexible production capability.” Such a connect of system paradigm that relies on customers’ requirements is influenced by the characteristics of the manufacturing environment with the sustainability consideration, duly defining functional, cost, quality requirements vis-a-vis lead time of products and also personalization. Agile manufacturing has thus been advanced as the answer to the imperatives of a new industrial paradigm characterized by an unpredictably changing market environment. Bi posits a new challenge should emerge as to how an existing paradigm may be modified so as to accommodate the requirements of sustainability. Possibly, Fig. 3 provides a way out.

Figure 3.The Input-Process-Output Diagram (P-diagram), Presently in the System Thinking Form, as Controlled by Capability (Current State). Here the Ambition (Unbridged Gap from Current State) is a Preferred Target for Matching (Opposite of Elimination)

Figure 3.The Input-Process-Output Diagram (P-diagram), Presently in the System Thinking Form, as
Controlled by Capability (Current State). Here the Ambition (Unbridged Gap from Current State) is
a Preferred Target for Matching (Opposite of Elimination)

Back to system thinking, while reconsidering the paradigm of matching ambition and capability, as in Fig. 1 of Part 1 future of cars, and integrating with the IPO part of Fig. 2 above, a new type of ‘P’ (process) diagram is seen to evolve, duly controlled by controllable factors (as capability) and the noise (as ambition). Such a diagram is shown in Fig. 3. The difference is, however, envisaged in the substitution of noise versus the ambition. Noise is unwanted and the process is thwarted to keep it at bay. On the contrary, the ambition is generally chased for eventual realization. However, in case capability is lacking, for pursuance of present equilibrium and sustenance, the ambition may at times be kept at bay. But since the processes are subject to change and thus made conforming with respect to evolution, the directions of arrows has been realigned in the new transform.

Further, since the impetus of sustainability is ongoing, and shall continue to enforce innovation and action, the current technological revolution (CTR) must, therefore, continue to seek investments. To increase current capabilities in line with aspirations of industry, the system thinking may be progressed considering the limiters as operates the noise. The P diagram may therefore be considered in the new form connecting capabilities and ambition matched through system thinking, as in Fig. 4.

Figure 4.The (P-diagram), Depicting Input Process-Output Diagram Connecting Capability and Ambition Managing Progress and Abating Limiters for Success

Figure 4.The (P-diagram), Depicting Input Process-Output Diagram Connecting Capability and
Ambition Managing Progress and Abating Limiters for Success

The aforesaid deliberation for upgradation of capability, in line with mission (ambition), deserves a systemic approach. It is likely to utilize a dynamic knowledge development and application framework. Argue Harkins and Moravec the futures-relevant system’s paradigms which explain the knowledge frame work involves following salient:
1. Mechanical (conservatively repetitive) where knowledge is produced in controlled amounts accidentally (as a serendipitous discovery),
2. Evolutionary (self-organizing) produced continuously, but with unclear applications, and
3. Teleogenic (purposively creative); produced in great amounts, but judged according to fit with trends, designs, markets, and customers.

Harkins and Moravec define knowledge as decision-applicable transforms of information that serves in competitive national and global contexts, and is applied to manufacturing in present context.

The potentials of such knowledge multiplication for subsequent application to manufacturing were discussed in previous parts of this four-part series, and calls for an approach that promotes due grounding with competence. This requires a taxonomy defined by higher level thinking.

Further, for the sake of competence, envisaged for Indian manufacturing as in Make in India paradigm as proposed by Prime Minister Modi, it possibly calls for total competence in production and operation research. The implied objective is radically improving the way manufacturers thread processes and systems in the entire product value chain.

Grounding of New Design Directions for Manufacturing

Interpreting data from industry reports and case studies, Tennant et al. envisage: by 2020/2030 manufacturing will predominantly emphasize process and material efficiency toward complete sustainability solutions, as there will be financial and resilience drivers to do so. This, as a consequence, argues the National Science and Technology Council’s (NSTC) plan documenting “the fundamental importance of advanced manufacturing” will improve the nation’s competitiveness. The trend of use of high technology is already favored as evidenced in Fig. 5.

Figure 5.Sustainability and Competitiveness for Hi-Tech Processing

Figure 5.Sustainability and Competitiveness for Hi-Tech Processing

Figure 5 also warns of an erosion in output of American manufacturing. This is despite the manufacturing productivity growing by 32% between 2000 and 2010. Robert Atkinson, author of report of Information Technology and Innovation Foundation (ITIF) attributes this to non-replacement of low value-added manufacturing with high-value added manufacturing, or non-opening of new plants to replace closed ones. The trend is historic as well as global as other industrialized high-skill nations are also falling behind in manufacturing, he observes, while the demand has stayed robust. About plant closures since 2000 in USA, a net 60,300 manufacturing plants closed, or 15 per day. Such a trend helped invent a manufacturing versus making paradigm (e.g., Make in India), where the latter tends to provide design competencies, and benefits of innovation, and use someone else for manufacturing.

India has a similar story to tell, though the reasons may be different and varied. Those include thefts, envy, wrong costing, and lack of judgement for competitiveness. Of the factories that closed, many of them gave way to raising engineering colleges, marriage palaces, and shopping malls.

Exhibit I.Product Evolution in China
China has developed product know-how because of its strong position within manufacturing as a location for outsourcing, and that knowledge flows unidirectionally from outside into China to support related innovation. A second opinion is that the information technology revolution allowed the process of manufacturing to separate from the innovation processes of R&D, product definition, design, branding, and marketing. Neither of these link innovation and manufacturing, however, which Nahm and Steinfeld argue is the key factor to China’s rapid advancement in manufacturing.
“Innovative manufacturing” takes into account the possibility of proprietary know-how and specialization (innovation) being embedded in the fabrication and assembly process itself (manufacturing). China’s particular form of innovative manufacturing specializes in rapid scale-up and cost reduction, with globally unparalleled skills in simultaneous management of tempo, production volume, and cost. Consequently, production is able to scale up quickly and with drastic reductions in unit cost. This has enabled the nation to expand even in industries that are highly automated.


China, however, presents a stark contrast. From a dismal 5.7% of the global manufacturing output in 2000, China gained an impressive growth to a new high of 19.8% in 2011, the highest in the world. Nahm and Steinfeld assess the contribution of innovation in this growth is well attributed besides having accounting for the low production costs gifted in China’s favor. Concur Breznitz and Cowhey; the product evolution occurs outside US (see China case in Exhibit I) call it Making, and the manufacturing as a service is undertaken in China. The gap in Fig. 5 also corroborates US’s strength in innovating technologies. To correct this US looks forward to integrate innovations from universities and R&D labs (termed pipeline innovation) and the incremental innovations contributed by industry. The premise is supported by excerpts from Deloitte Manufacturing Competitiveness Index (Deloitte Council on Competitiveness 2010) which measures talent-driven innovation at 9.22 on a scale of 10, in contrast to manufacturing innovation at 6.62. This also corroborates that the contribution of academic and research bodies together is radical vis-a-vis the contribution of the industry. Further possibly, the lack of integration in academia’s and industry’s individual research directions corroborates the large gap shown in these two standards of 9.22 versus 6.62 respectively.

Such innovation-organization’s reform is considered a prerequisite to implement new manufacturing technology paradigms. Endorsing ‘Manufacturing Matters,’ Helper et al. view manufacturing remains the major source of commercial innovations which is also essential for innovation in the service sector. Additionally, as manufacturing makes a disproportionately large contribution to environmental sustainability, it remains in line with larger objectives of sustainability management (SM). Thus, to abate the sustainability pressures, resorting to ‘making’ instead of ‘manufacturing’ is also one factor considered by industries for assigning manufacturing to developing economies characterized by cheap labor. ‘Making’ is hierarchically superior to manufacturing, given as Swamidas views the “Competencies derive less from specific technologies or manufacturing facilities and more from manufacturing infrastructure composed of people, management and information systems, learning, and organizational focus,” who has the latter rule the roost.

An additional imperative that hides in between the gap connecting ‘making’ and ‘manufacturing’ is the schema which enables decision making over people, processes and machines (held by another manufacturer or in other country) is another character of the nextgen manufacturing.

Given that the interconnection between making and manufacturing is, therefore, of both soft and hard nature, this invisibility is set to be handled by the IT. Nikkei Monozukuri, in the foreword to 3-D Manufacturing Innovation, visualizes that it is the soft components that provide the “invisible competitive edge” in the business process. On the other hand, the hard contributors which are visible at the end of customer call for a product design development and improvement idea driving innovation at the making center.

Technically, manufacturing is dependent upon 3-P’s, viz., the people, processes, production planning and control. On the other hand, making is more influenced by 3-D, viz. design, decision, and development; for the former, capacity and capability are important.

Thinking in Harrington Emerson’s way the “overall equipment effectiveness (OEE), as proposed by Seiichi Nakajima in the 1960s, serves as the hierarchy of metrics used to evaluate how effectively a manufacturing operation is utilized toward Lean Mean and Green operations as a roadmap for sustainability management. It measures efficiency × availability (say of machine tools)”.

Bi posits manufacturing systems become more and more complicated due to the expanded activities and the dynamics of manufacturing environment. Li and Mehnen count the stance of cloud manufacturing into the new scope. Since manufacturing is evolving as more of a mechanized transformational technique to add value precluding society’s overall interests, I followed up how “Modern day ethical dispositions value dimensions of safety and environment more than quality and productivity.”

Evidently, manufacturing is contemplated to improve the quality of life, which follows the basic tenets of the existence of the fact of “life.” From the angle of value chain perspective also, while analyzing the trends in global manufacturing, Rodrigue et al. stipulate that future developments in global manufacturing will be complemented by the enhancement of capabilities related to innovation, labor and infrastructures. The schema calls for due flexibility in use, which are made concurrently available 24×7× 65 through cloud. While the soft and hard systems are encompassed along with the domain of cyber physical systems-a set of control equipment over internet-the system of cloud enables much higher capatence (capacity + competence) making manufacturing cost effective.

Cloud as a Pillar of Next-gen Manufacturing

Given that the manufacturing industry is the mother of a healthy society, and the making and the manufacturing getting matured in disparate directions, the interspersing of cloud technologies can facilitate a collaborative environment that can give people agility, more transparency, and empowerment. In a scenario when manufacturers are under constant pressure to increase accuracy, make processspeed a competitive force, they tend to capitalize on their internal intelligence and knowledge by incorporating every interaction between suppliers, distributors and services for improvement .” This is especially applicable to the high-tech, industrial and aerospace and defense industries, where rapid product lifecycles and short time-to-market schedules are commonplace.

Emphasizing on solutions, provides Kunio, “Solutions play an important role in transforming enterprise systems, contributing to cost reduction, agile deployment of services, expanded flexibility and improved productivity.” Well, cloud is a logical facility that is built, hosted and delivered through a soft computing platform over the Internet. Cloud servers possess and exhibit similar capabilities and functionality to a typical facility, but are accessed remotely through the service provider. Their operability adapted to ‘‘manufacturing’’ by lateral thinking imparts it a logical (and natural) manufacturing competency environment in the new millennium, which is increasingly IT-reliant, agile, globalized, with high reliability, scalability and availability in a distributed environment.

Tipped as service-oriented, customer-centric, demand-driven manufacturing model, NIST defines cloud manufacturing as ‘‘a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction.” It leads to enhanced efficiency, reduced product lifecycle costs, and allows for optimal resource loading in response to variable-demand customer generated task in.” This helps show an exemplar from the world leader in stainless steel sinks, water coolers and kitchen cabinets manufacturing- Elkay Manufacturing Company-which has successfully adopted and benefited from cloud computing technologies. Morley evaluates how cloud computing will benefit the manufacturing industry, when connected for full functionality in an agile way and with minimum resources being applied. Since cloud environment encompasses three core components, Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and finally Software as a Service (SaaS), these three components have the ability to replicate an entire behind-the-firewall IT environment within a hosted or cloud-based environment. Such SaaS type applications are adapted ERP system in the cloud, e.g., SAP with their business by design. As per a 2013 survey by Jutras of SaaS adoption in manufacturing, distribution and other industries SaaS-based applications are used by 22% of all manufacturing and distribution software, and will grow to 45% within ten years.

Being in a multidisciplinary domain that centralizes operation management of the services, cloud manufacturing provides a seamless, stable and high-quality transaction of manufacturing resource services. Thus it encompasses networked manufacturing, manufacturing grid (MGrid), virtual manufacturing, agile manufacturing, Internet of Things, and of course cloud computing. In a typical distributed manufacturing environment, the resource service provider and resource service demander have little coordination. On the other hand, in cloud manufacturing, collaborations can happen at a much broader scale encompassing enterprises or nations. It thus reflects both the concept of will integration of distributed resources” and the concept of “distribution of integrated resources”. Sums up Industry Week “Connected enterprise is a foundation upon which to build great things,” say, “The connected enterprise is not just a revolution, it’s an evolution. It sure has the potential to bring make and manufacture to a new renaissance.”

It was argued above that in order to be futuristic, the constructs of ‘manufacturing for competence’ journeying as the ‘connects’ in Fig. 2, through the three apexes are in need of continual progressing both in terms of action and innovation. In their editorial Sinderen & Almeida envisage that “In order to cope with legacy and heterogeneity problems and consequently with [a] lack of interoperability, considerable research efforts have been spent on integration of otherwise isolated systems either within the scope of a single organization or across organizational boundaries” (‘a’ has been appended to claim that there is a concerted devotion toward envisaged competencies). We continue with the grounding phase of postulation to Industry 4.0, and attempts to seek the ‘state of art’ in each of these directions/sub-directions. Firstly, we assess the state of innovations in IoT (Internet of Things) era and evaluate the role of cloud facility toward Industry 4.0, manufacturing state. The cloud is a resource set to harness global availability of goods and services effectively. After its due consideration and applicability to manufacturing, we then need to see how action and innovation should guide each of these initiatives, viz., quality and sustainability in marketplace. Understanding their role is an imperative, whereby manufacturing should prosper on the basis of the coveted competencies, which need a dedicated research in manufacturing (Make in India style), and productivity. For every activity, requisite sets of tools and techniques are required to resource the competency enhancement to meet both the designated objectives and for the ‘state of art’ in future wetware technologies, viz., HSLD-industrial control systems, and the thematic development of cloud to facilitate manufacturing in action and innovation.

Metamorphosing Cloud to One Compatible with Industry 4.0

Cloud-based strategies enable collating their own innate intelligence and knowledge into every sales (including production) situation, to the extent that these create epiphanies, such that these are quicker to roll out, easier to customize and offer high adoption rates across customers/ consumers. Columbus counts ways organizations use cloud computing to revolutionize manufacturing, and free up time to invest in new products by streamlining key areas of their business. The ways in which cloud computing is exploited in manufacturing is tabulated in Exhibit 2. Evidently, computer as a tool (controlling IoT), and cloud as a resource help improve the platform which facilitates industrial controls over high speed and long distances. To win the future skills race and meeting challenge, it is vital to understand how cloud technologies may span multiple sets of manufacturing roles with advanced technologies and materials. A report by US Council on Competitiveness posits the areas to harness next-generation productivity using smart innovation and next-gen manufacturing, advising:
1. Industry and labor should develop state-of-the-art apprenticeship programs for 21st century manufacturing, while
2. Creating national advanced manufacturing clusters, networks and partnerships, by
3. Prioritizing R&D investments, deploy new tools, technologies and facilities, and
4. Accelerating commercialization of novel products and services.

How all these options are facilitated is endorsed in Exhibit 2.

The idea of “capturing domestic competitive advantage in advanced manufacturing” is expected to promote investments therein with potential to transform industry. The Advanced Manufacturing Partnership Steering Committee proposed that a national advanced manufacturing strategy be established to secure a sustainable resurgence therein. This will put in place a systematic process to identify and prioritize critical cross-cutting technologies. The committee proposed to create a searchable database of manufacturing resources which support a key mechanism to access enabling infrastructure, toward which resourcing of IIOT and cloud would offer immense opportunities for a manufacturing renaissance. It is to ensure that one reacts quickly and efficiently to changing markets, recommends the 21st Century Manufacturing Enterprise Strategy report.

Exhibit 2.The 9 Ways Organizations Use Cloud Computing to Revolutionize Manufacturing

Option Explanation
Capturing and applying company-wide intelligence and knowledge Cloud-based platforms are used for managing rules exploiting mobility support for analytics, business intelligence and rules engine reporting and analysis.
Full launch of supplier portals and collaboration platforms High tech who have implemented Vendor Managed Inventory (VMI) and demand management applications by piloting and then moving quickly that deliver real-time order status and forecasts
Designing in services for targeting cloud integration expertise Integration of varied services, voice-activated controls, iPhone, all integrated to the cloud including emergency assistance availability, say in the latest luxury cars, used for new product generation with embedded services
New product development and introduction (NPDI) for enhancing time-to-market strategies Time-to-market constraints are requiring greater collaboration earlier in design cycles
Managing and tracking of channel performances Direct and indirect channel performances (of person) and profitability controlled from a single cloud platform, thru dashboards reports. Performance (of deals)
Marketing automation applications to plan, execute and track results of every campaign Marketing automation applications help companies align their internal content, strategies and ability to execute with the potential these marketing systems promise
Integration of support and service systems; for functional management. Manufacturing industries use levels of high tech to get cost and time advantages for automating self-service at varying levels of adoption
Automated customer service, order status inquiring platforms pricing, of content management, etc.
Cloud-based ERP systems facilitating two-tier ERP strategies Cloud-based ERP system is adopted by manufacturers for pursuing two-tier ERP strategies which abate dependence on monolithic ERP systems that may fail over distributed geographic regions, or require intensive programming for re-customization. This is expected to allow greater efficiencies in material planning, supplier management and reduce logistics costs
Cloud-based human resource management (HRM) systems for harmonization Includes combining multisite talent management, recruiting, payroll and time tracking. Contract manufacturer Flextronics uses work day to optimize work force allocations across their global manufacturing centers, for example. To unify all manufacturing locations


The need of competence, for surviving and prospering in a competitive environment of continuous and unpredictable changes calls for agility in providing customer-designed products and services. Bozdogan provides the
way out. By gaining both conceptual traction and practical relevance, it enables viewing enterprises as purposeful complex adaptive systems. Bozdogan further recommends adopting the construct of enterprise architecture as a central conceptual framework toward developing effective future transformation strategies.
* The report on Emerging Global Trends in Advanced Manufacturing issued by Science & Technology Policy Institute (STPI – part of the Institute for Defense Analyses), foresees new frontiers in next 20 years. It visualizes an increasingly automated and data-intensive manufacturing sector that will likely replace traditional manufacturing. This report on Advanced Technologies Initiative by Deloitte and the Council on Competitiveness (Council) highlights five converging overall trends, viz.:
Rapidly proactively changing manufacturing systems in response to customer needs and external impediments.
* Reliance on modeling and simulation in the manufacturing process.
* Ubiquitous role of information technology.
* Acceleration of innovation in supply-chain management.
* Fully supporting sustainable manufacturing.
* This will be met through emerging technologies, viz., additive manufacturing (aka 3-D printing) and biomanufacturing with a focus on synthetic biology. Report argues most of these trends are not simply technological, but have organizational and business-model focus as well. There is a renewed focus on integrated computational materials engineering.

On the technology side, the report notes major advances in two mature areas which are, say, semiconductor fabrication and advanced materials. The fact is endorsed as in NIST reports the federal government chose four categories of investment “to position promising, nascent technologies for broad adoption and commercialization” as under:
1. Advanced materials
2. Production technology platforms
3. Advanced manufacturing processes
4. Data and design infrastructure

The appendix of the strategy also contains a skills competency model framework for advanced manufacturing. Li and Mehnen exemplify a near-real-life simplified shop floor that consists of typical manufacturing objects. It is a referenced infrastructure of ubiquitous manufacturing (UM), in which a smart gateway and a real-time work-in-progress management system based on smart objects such as RFID/Auto-ID devices and web service technologies are designed to improve the optimal planning and control of the entire shop floor. Manu Cloud is one cloud-based infrastructure that provides better support for on-demand manufacturing supply chains in automotive sectors and also in PV (photovoltaic) and organic lighting. Lu visualizes a hybrid manufacturing cloud to manage their periodic business goals, which are supported in the system by a set of private cloud, community cloud and public cloud and effectively manage access to the resource through self-defined access rules such that unauthorized companies cannot intrude. To manage these user-defined clouds, a cloud management engine is put forward which may use semantic web technologies as the main toolkit for managing resource access.

All such above-cited expansions in activities and dynamics of manufacturing environment make latter more and more complicated. But targeted quality-driven response strategy in cloud may help organizations reposition themselves to enhance the capability of operation systems and help organize for sustainable development. It is recommended that the resources at all levels must work together so that system reconfigurability can be maximized, cost-effectively. At lower levels, reconfigurability is managed by changing methods or adapting organizations. This is further achieved by aligning systems with resources which are software, wetware and hardware at higher levels extending to lower levels respectively.

The ‘State of Art’ In Competent Sustainability and Quality

Herrmann et al. (2004) perch that knowledge base of best practices help support systematic concept generation for effective platforms that may replace obsolete technologies and parts with newer parts, when the former get supported by design for manufacturing (DFM) tools to develop product platforms. They weigh the whole exercise as being prohibitively expensive. However favored by the analysis of system viability, and understanding of the application of ‘design refresh planning’ one can help quantify and reduce the cost of sustainment. Since viability is a measure of producibility, supportability, and evolvability of a system and it holds the key to achieving a competitive manufacturing business, it reliably acts as a metric for assessing both sustainability of a product and technology-insertion opportunities. Hence enterprises are increasingly becoming aware that their ultimate success is no longer built around a firm’s capability and capacity to achieve efficiency, effectiveness, flexibility, and creativity, but on that of supply chain that facilitates meeting of the strategic objectives of sustainability management (SM).

Given that sustainability of economy, society and environment has been recognized as a priority in fundamental engineering research, all metamorphosis of people and of glocal value chain systems are poised to undergo a transformation to change from its traditional management approach to SM. The facilitation for transformation emanates from deployment of quality management (QM) principles coupled with sustainable development. I envisaged a zero-waste culture (as an organizational) … paradigm to sustainable progression … to maintain it in fitness mode. The solution is through a higherlevel cognizance to win-win. That is, a system as a whole needs to be sustainable. Cohen et al. assert sustainability metrics are quantifiable and easily measured, but Bi, the metrics of sustainability have not been quantified, and their residual relations to design parameters of a manufacturing system
also need to be established. Jawahir et al. posit sustainable manufacturing is not just about manufacturing processes or the products, but form a multi-level approach on products, processes, enterprise and supply chain, as a system. This is in line with the ambitions of US Department of Commerce that sees sustainable manufacturing as the creation of manufacturing products that use materials and processes that minimize negative environmental impacts, conserve energy and natural resources, are safe for employees, communities, and consumers and are economically sound.

Bi endorses the requirements of sustainability are ubiquitous, with customers’ requirements, governance and regulation, public values, environmental priorities, and increasing energy costs as major drivers. The shortage of natural resources, manpower, and energy are other issues asserting in favor of better qualte-k-nology initiatives, duly exemplified through direct consolidation of steel swarf and strategic development of, say, aluminum-lithium alloys. Obviously, knowledge and technology are no more important than quality. As Peter Drucker clarifies, “Quality in a product or service is not what the supplier puts in. It is what the customer gets out and is willing to pay for.” Any ‘loss a product imposes on society after it is shipped’ owes to manufacturer, quips Genichi Taguchi. His definition of quality is aptly based on a more comprehensive view of the production system, which is another objective for next-gen manufacturing.

Necessarily, “advanced manufacturing enterprise begins with modeling and simulation [with] an agile supply chain capable of rapidly responding to both upstream changes such as resource prices and downstream changes such as demand.” Shipp asserts “the smart factory utilizes sophisticated applications to optimize production efficiency and quality control.” The future manufacturing systems, therefore, have to be evolved to meet emerging needs either from the customers or from the manufacturing environment. For example, Vaucouleur discusses the evolvability of enterprise systems, considering this quality dimension for enterprise resource planning systems in particular. The author puts forward the argument that anticipation of possible evolution is not a panacea and that mechanisms to cope with unforeseen upgrades to enterprise systems are thus required to enable evolvability. To face this challenge, the Vaucouleur proposed an aspect-oriented mechanism to customize an existing system. In connection with evolution of quality manpower, I argued it has “to go through an evolutionary process.” Appraise Snee and Hoerl the “century of quality and job creation can be achieved through, among other advances, addressing the inevitable role of human variation in innovation.” Similarly, my mapping for manufacturing people reads: “the Quality will … become a coercion. But first it has to become a compulsion, a norm, one preceded by Awareness….” And this awareness is implicit for all, customers, operators, and leadership et al.

The paradigm calls for a radical change. William laments: “We must begin to truly think differently about things we assume we already know quite well. Take customers, for example we think we understand them well already, but we don’t. …we are at the dawn of a new era of customer understanding and [yet we are un] able to keep pace with changes in the nature of customer demand, and it is a field that is changing perhaps faster than any of us realize.” Such behavior determines that the interfaced sustainability managed “quality-driven response strategy [sh]ould help organizations reposition themselves and enhance the capability of operation systems for sustainable development”. The answer lies in a thorough reengineering of manufacturing competence. And it must be systemically invoked managing input and processes.

The Conscience of Action and Innovation

Until a group is constituted and agrees to take action, no innovation can result, especially when it triples while following as a helix as in Fig. 1. Thus there is “a strong need to address evolvability during the whole lifecycle of the system” [while] “obtaining better insights in and control over the corresponding processes.” Visualize Sinderen and Almeida exhorting: “complex business processes have to be designed with performance and quality goals in mind.” Especially in case any enterprise system is run at reasonable costs, action and innovation deserve a boost. To increase productivity, reduce costs, improve quality, and thus strengthen their position relative to competitors, it is implicit business and software development processes are strategically improved. Observe Vachhrajani and Vachhrajani “The innovation landscape is changing rapidly. Innovations are becoming more and more inclusive and rapid. They are transforming lifestyles and empowering customers to create value for them, as perceived by them.” Implementation, however, requires a concerted action as “Organizations are made up of people and what counts is not their number but their brains, i.e., capability of exhibiting original thinking-call it a radically different way of thinking/organizing (or a paradigm).” In fact, it takes time and focused effort for enterprises to shift their paradigms and integrate innovation with action into their business strategies and cultures. In present case, “The paradigm of manufacturing therefore is the genesis of the factoring of customer requirements to yield high-quality low-cost products efficiently and productively to meet exacting schedules and priorities. The methods employed should be kind on raw materials and other resources, inputs impacting environment including energy, forest-wood, mined products, etc. The net manufacturing competence is thus a trade-off between the results in transformation obtained and the costs of achieving requisite gains”. The modus operandi of combining action with innovation is attempted in a previous work around metal casting which sees “a newer paradigm over the road map for present growth, development, invigoration, idealization and innovation [that] sets in the enabling of forecasting the trajectory (direction) of metal casting industry. [Thus] An opportunity of correcting the technological progression and augmentation of competencies (while narrowing technological competitiveness) exists amply.

The writing on the wall is clear. And it is: (i) Develop your (manufacturing people), as a mother does to her child; (ii) Hurry up translating learning into skills, and technology into facilities; (iii) competency for innovation; and (iv) forecasting for meeting unprecedented challenges to maintain competitive positions. The Chak De! success envisages a strategic planning, and team work.” For, a high-quality leadership is sought for “team work,” training (thru trials) and transformation.

Teaming up to total transformation is invigorated because “on a higher hierarchical level, it is process capability in designing, reengineering design changes and product improvements and process rejuvenation for a great product! Teams provide a collaborative environment that can give people agility, more transparency, and empowerment through more effective collaborations. At a still higher level, it is the organizational competence to display a product worthy of that of being expected out of a world-class [organization], which requires a culture for innovation.”

To help establish the foundation of an innovative culture, Marisa Brown, subject expert, product development and innovation at APQC, advocates the deployment of overarching cultural frameworks and well articulated strategies with transparency. She guides the recommendations as in Table 1 must be facilitated with due roadmaps and guide posts to provide direction and impetus for action and innovation.

Table 1.The Requirements for Grounding Innovation Culture in an Organization

Thematic and Leadership Contributors & Resources Schema and Strategies
Visible participation and active involvement from leadership at all levels Designating physical and/or virtual spaces dedicated to innovation to creative thinking. Internal initiatives competitive environment, for innovative thinking and provide recognition
Encouraging employees to collaborate for idea generation and problem solving. Employing a diversity of communication vehicles for a relentless focus on innovation. Allocating resources depending on the amount of risk involved.
Collaborating through internal and external alliances Proper selection of software tools Risk taking for letting innovative culture thriving
Hiring employees with criteria of innovative culture outside of functional capabilities Establishing innovation specialty groups to broaden engagement. Knowledge and change management techniques can facilitate the embedding of innovation.


Vouches William Troy, CEO, American Society of Quality, through his Introduction to ‘The Future of Quality: Quality Throughout’ argues: “The implications of almost limitless connectivity will change how we think about, and do, almost everything.” Falling in line with the butterfly effect ‘everything affects everything else,’ feels Troy “This is not really true today, but it will be tomorrow. From the connectivity that is an essential part of smart manufacturing, …a crisis in one sector can be immediately identified, communicated, and reacted to in seconds, affect [ing] everything else, both for better and for worse.”

This becomes an opportunity for action and innovation because as a consequence of the humans’ unique ability that transcendences experience earned in one domain of life, and after extraction of lessons those get applied to an entirely different domain of their existence. Moreover, the phenomenon is systemic, and follows the modus operandi vide, say, a type of models schematically illustrated above. Breja et al. envisage that to gain competitive advantage through the systems approach, the business organizations need to master challenges like (1) maintaining strategic focus (viz., for a limitless connectivity), (2) matching strategic options with aspirations (say ambitions), for which it is necessary to (3) align the human resource to match their mission with that of the vision of their organization, and (4) to work for a total organizational transformation, or rather metamorphosis of people, processes, and even systems.

Meir Ben-Hur asserts their branching (of knowledge interface) laterally to a different application becomes much easier through applying similar tools and concepts, and this becomes the modus operandi of futuristic directions in production engineering research. Simultaneously, the research directions get wide spread. The [knowledge] life cycle concept exhibits advancement of [knowledge learning to] maturity phase with respect to people’s awareness/perception or technology benchmarks, explored through Thareja’s conceptual model for knowledge innovation. It is helped by a process of iterations right from the earliest stage of design which can not only provide early estimates of downstream metrics but also help link performance metrics directly to intended function.

Through a pre-production, production and post-production of manufacturing organization and their interrelationships Nookabadi and Middle proposed a conceptual generic quality management model consistent with systems development processes, where the three phases fulfill following roles as implicit requirements:
1. The preproduction phase should ensure that the product that has been developed meets customer requirements and can be produced fast, defect-free and reliable.
2. The production phase should ensure that quality and reliable product is produced fast and is made available when needed.
3. The post-production phase should ensure that produced quality and reliable product is delivered on time and defect-free.

In an environment devoid of boundaries in which companies gather to achieve a common goal, any such initiative will significantly enhance and strengthen the ability of following:
1. Shortening of product development cycle time; the product is rapidly brought to market.
2. Reduction of product costs.
3. Making customer-chosen options reconfigurable and upgradeable.
4. Offering individualized goods and services.
5. Enabling ever-changing models, with longer-lived product families.
6. Replacing mass markets by niche markets.
7. Forming flexible organizational structures in response to economic opportunities and challenges.
8. Enabling organizations to participate simultaneously in various forms of virtual enterprises.

As a corollary of knowledge-learning as above, “new information becomes part of a coherent conceptual structure,” which should become our natural approach to systemically integrate knowledge for desired change in manufacturing-natural because it must address achievement of economic development, environmental performance, and social equity. Rodrigue et al. stipulates global manufacturing; from a value chain perspective it impacts on three fundamental pillars: factors, standards and costs. For making a paradigm work, these factors need be implemented simultaneously with sustainability for competence guided by zero-defect zero-effect. It calls for integrating quality and environment with sustainability management toward total business integration.

1. Development of manufacturing has transformed from competitiveness toward the aspirations of a beyond-competence phase called Industry 4.0, which may be approached by 2035/2039. It is presumed that even at such a stage, this will still remain at war with eco-sustainability / management. Hitherto, system thinking has successfully allowed incorporation of developments in allied fields, viz., IoT (Internet of Things) @ Industry 4.0, to enable through Industrial Internet of Things (IIOT), but has not really bridged the quick transfer of innovative products developed at universities and research laboratories.
2. Sustainable manufacturing has been a constant call for manufacturing renaissance within the last few years. But the impetus has grown into a large realization for the effectiveness of sustainability management’s implementation. This is defined by the paradigm of zero-defect zero-effect-a made in India product.
3. Cloud is being used to service a manufacturing system. Multiple companies may deploy manufacturing resources for sustainable management over the Internet providing a cost-effective, flexible, and scalable solution to global manufacturing.
4. The need for system thinking has been postulated over the series, which advocates due action with innovation for success. System thinking may be invoked, practicing modeling and simulation. The end objective is a competitive
5. The practicality and implementation imperatives of cloud manufacturing in this work endorse that it has a large contribution to transform current manufacturing to Industry 4.0 era.

Dr. Priyavrat Thareja
Dean, Faculty of Engineering & Technology

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