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Despite the potential of SMEs in economic development, their activities have remained largely unsustainable in Nigeria. These enterprises are constrained by a number of challenges- high cost of production, poor power supply, high infrastructural deficit etc. which have made there operations largely unproductive. The purpose of this paper is to examine the effects of production subcontracting forms on the sustenance of small and medium enterprises as a panacea for achieving the targets of goal 8 of sustainable development goals (SDGs) in Enugu State, Nigeria.

The paper adopted a number of methods comprising of field observations, a reference to relevant literature and a questionnaire survey of 96 SMEs. The paper also adopted a quantitative approach comprising of simple descriptive statistics of mean and standard deviation as well as regression analysis to analyze the data.

This paper found that the three forms of production subcontracting (supplier, specialized and capacity subcontracting) identified in the paper were used by SMEs to achieve sustenance (cost reduction, risk reduction and access to resources) in their operations. The paper suggests that the sustenance of SMEs through the utilisation of the different forms of subcontracting can become a strategy towards achieving the targets of SDG 8 in Nigeria.

This paper has shown that the prevalent high cost of production and ever-increasing production risks, which are the common features of SMEs in Nigeria, can be mitigated through the various forms of production subcontracting analysed in this paper. SMEs, through seminars, workshops, entrepreneurship and business fares, can be encouraged to take up this strategy, considering its ability to address their various operational bottlenecks.

This study adds to the limited available evidence concerning the effects of subcontracting forms on the sustenance of SMEs in Nigeria. This study is the first to consider subcontracting forms and how they have led to sustenance SMEs in Nigeria.

The purpose of this paper is to consider various possible constraints of the problem of production and maintenance planning control for a multi-machine under subcontracting constraint, in order to bring the manufacturer industry closer to real mode. In this paper, we present an efficient and feasible optimal solution, by comparing optimization procedures.

Our manufacturing system is composed of parallel machines producing a single product, to satisfy a random demand under a given service level. In fact, the demand is greater than the total capacity of the set of machines; hence there rises a necessity of subcontracting to complete the missing demand. In addition, we consider that the unit cost of subcontracting is a variable depending on the quantity subcontracted. As a result, we have developed a stochastic optimal control model. Then, to solve the problem we compared three optimization methods: (exact/approximate), the genetic algorithm (GA), the Pattern Search (PS) and finally fmincon. Thus, we validate our approach via a numerical example and a sensitivity analysis.

This paper defines an internal production plan, a subcontracting plan and an optimal maintenance strategy. The optimal solution presented in this paper significantly improves the ability of the decision maker to consider larger instances of the integrated model. In addition, the decision maker can answer the following question: Which is the most optimal subcontractor to choose?

The approach developed deals with the case of the real-mode manufacturing industry, taking into consideration different constraints and determining decision variables which allow it to expand the profits of the manufacturing industry in different domains such as automotive, aeronautics, textile and pharmacies.

This paper is one of the few documents dealing with the integrated maintenance in subcontracting constraint production which considers the complex aspect of the multi-machine manufacturing industry. We also dealt with the stochastic aspect of demand and failures. Then, we covered the impact of the unit cost variation of subcontracting on the total cost. Finally, we shed light on a comparison between three optimization methods in order to arrive at the most optimal solution.

This study aims to provide a foundation for the development of subcontracts that suit takt production in construction.

This is a non-empiric conceptual study, which integrates takt production and general construction literature into new proposals for subcontract clauses suitable for takt production in construction. This study uses literature reviews, from which proposals regarding takt production viable subcontract clauses are conducted via logical reasoning.

A total of 13 proposals for takt production applicable subcontracts are provided in this study. The proposals emphasize detailed and collaborative planning, suitable payment methods and flexibility for takt plan modification.

Previous takt literature has not properly addressed the development of subcontracts for takt production, despite regular attempts to use subcontracting in takt production. This study aims to aid main contractors to create fair and suitable subcontracts, so that adhering to takt schedules could be more viable in practice. This study also acts as a foundation for further empirical studies regarding the subject.

In 1986 a study was carried out in a number of small companies in the UK that manufacture to customer requirements. The primary objective was to assess the relevance and importance to industry of ideas developed in earlier research at Lancaster University, relating the order quotation process to production and sales. However, in the course of the study a great deal was learnt about the industrial sectors examined.

Presents work that addresses the issue of decision support for the operational management of subcontract manufacture. Theoretical study has been combined with empirical research and practical industrial investigation with regard to distributed manufacturing systems which incorporate subcontract manufacturing arrangements. There has been a particular focus on the study of resource planning and scheduling for subcontract manufacture in SMEs in the UK electronics assembly industry. This work led to the analysis, modelling, implementation and test of an object‐oriented advisory system to assist with scheduling for this domain which demonstrated the utility of a proposed concept of captivity‐based scheduling. Contemporary research in this area and existing commercial decision support solutions for manufacturing planning, scheduling and control in SMEs have been explored. Concludes that current commercial software systems for subcontract manufacture are underdeveloped. Further argues that software development tools and platforms are increasingly available to facilitate the creation of practical decision support systems for distributed organizational forms of manufacture.

Local networks of small- and medium-sized enterprises (SMEs) are founded both on collaborative and competitive inter-organizational relationships within the same network characterised by spatial proximity between firms. This paper aims to propose an original analytical framework to understand how spatial proximity between firms within local networks influences strategy of SMEs.

Theories and the existing knowledge were used to develop a preliminary conceptual framework. This preliminary framework was then developed as data collection and analysis were carried out. That is, in the more advanced stages of the research, both the literature and data allowed the design of a more specific analytical framework with the development of theoretical propositions. The data supporting the findings was derived from extensive content analysis of secondary documents from manufacturers, channel agents, industry organisations, public agencies and statistical sources. These data were also used as background briefing for 52 in-depth interviews with 36 senior managers within the sector.

An extensive qualitative research carried out in two major local networks of footwear production in Portugal shows that spatial proximity influences the following major variables of SME strategy: offer specialization, market specialization, competitive behaviour and collaborative behaviour. This paper examines the strong subcontracting relationships among manufacturers within each local network, discusses the competitive and collaborative behaviour of firms within their local networks of subcontracting and explains the nature of interaction between them contributing for a better understanding on the impact of spatial proximity on strategy.

Some management implications can be drawn from this research at the level of the network and of the firm, although both levels are profoundly intertwined. The paper discusses both these implications.

This research clarifies the relationship between spatial proximity and strategy of SMEs immersed in local networks. In particular, the findings show that, in the context of local networks of footwear production, SME strategy is influenced by spatial proximity between firms in the following characteristics of strategy: offer specialization, market specialization, competitive behaviour and collaborative behaviour. As it was discussed and empirically supported, spatial proximity between firms favour resource mobility, firms' interaction and reduction of transaction costs, which, in turn, impact strategy.

The purpose of this paper is to study various combination forms of the three basic sharing elements (i.e. orders sharing, manufacturers capacity sharing and suppliers capacity sharing) in the cluster supply chain (CSC), formulate a distributed model to protect enterprises’ decision privacy and seek to develop an effective method for solving the distributed complex model.

A distributed assembly cluster supply chain configuration (ACSCC) model is formulated. An improved augmented Lagrangian coordination (ALC) is proposed and used to solve the ACSCC model. A series of experiments are conducted to validate the improved ALC and the model.

Two major findings are obtained. First, the market order’s quantity change and the sales price of the product have a great impact on both the optimal results of the ACSCC and the cooperative strategy, especially, when the market order increases sharply, enterprises have to adopt multiple cooperative strategies to complete the order; meanwhile, the lower sales price of the product helps independent suppliers to get more orders. Second, the efficiency and computational accuracy of the improved ALC method are validated as compared to the centralized ALC and Lingo11.

This paper formulated the single-period ACSCC model under certain assumptions, yet a multi-period ACSCC model is to be developed, a more comprehensive investigation of the relationships among combination forms is to be extended further and a rigid proof of the improved ALC is necessary.

Enterprises in the industrial cluster should adopt different cooperative strategies in terms of the market order’s quantity change and the sales price of the product.

The proposed various combination forms of sharing elements and the formulated ACSCC model provide guidance to managers in the industrial cluster to choose the proper policy.

This research studies various combination forms of the three basic sharing elements in the CSC. A distributed ACSCC model has been established considering simultaneously multiple sharing elements. An improved ALC is presented and applied to the ACSCC problem.

The main contribution of this manuscript is to suggest new approaches in order to deal with dynamic lot-sizing and maintenance problem under aspect energetic and risk analysis. The authors introduce a new maintenance strategy based on the centroid approach to determine a common preventive maintenance plan for all machines to minimize the total maintenance cost. Thereafter, the authors suggest a risk analysis study further to unforeseen disruption of availability machines with the aim of helping the production stakeholders to achieve the obtained forecasting lot-size plan.

The authors tackle the dynamic lot-sizing problem using an efficient hybrid approach based on random exploration and branch and bound method to generate possible solutions. Indeed, the feasible solutions of random exploration method are used as input for branch and bound to determine the near-optimal solution of lot-size plan. In addition, our contribution to the maintenance part is to determine the optimal common maintenance plan for M machines based on a new algorithm called preventive maintenance (PM) periods means.

First, the authors have funded the optimal lot-size plan that should satisfy the random demand under service level requirement and energy constraint while minimizing the costs of production and inventory. Indeed, establishing a best lot-size plan is to determine the appropriate number of available machines and manufactured units per period. Second, for risk analysis study, the solution of subcontracting is proposed by specifying a maximum cost of subcontractor in the context of a calling of tenders.

For maintenance problem, the originality consists in regrouping the maintenance plans of M machines into only one plan. This approach lets us to minimize the total maintenance cost and reduces the frequent breaks of production. As a second part, this paper contributed to the development of a new risk analysis study further to unforeseen disruption of availability machines. This risk analysis developed a decision-making system, for production stakeholders, in order to achieve the forecasting lot-size plan and keeps its profitability, by specifying the unit cost threshold of subcontractor in the context of a calling of tender.

Focusing on the apparel industry, this study extends current knowledge on how additive manufacturing (AM) may impact global supply chains regarding structures of interorganizational governance and the industry's social-sustainability issues.

Following an exploratory research design, two consecutive Delphi studies, with three survey rounds each, were conducted to carve out future industry scenarios and assess AM's impact on supply chain governance and social sustainability.

The implementation of AM is posited to reinforce existing supply chain governance structures that are dominated by powerful apparel retailers. Retailers are expected to use the increased production speed and heightened market competition to enforce faster fashion cycles and lower purchasing prices, providing a grim outlook for future working conditions at the production stage.

Against the common narrative that technological progress increases societal well-being, this study finds that new digital technologies may, in fact, amplify rather than improve existing social-sustainability issues in contemporary production systems.

This article contributes to the nascent research field of AM's supply chain impact as one of the first empirical studies to analyze how AM introduction may impact on interorganizational governance while specifically addressing potential social-sustainability implications. The developed propositions relate to and extend the resource dependence and stakeholder perspectives on governance and social sustainability in supply chains. For managers, our results enrich the discussion about the potential use of AM beyond operational viability to include considerations on the wider implications for supply chains and the prevailing working conditions within them.

The study attempts to develop a multi-product multi-period (MPMP) aggregate production plan (APP) to fulfill the customers' demand in terms of throughput and lead time for achieving market competence.

This research proposes an integrated Fuzzy analytical hierarchy process (FAHP), multi-objective linear programming (MOLP), and simulation approach. Initially, FAHP is used to select the essential objectives a firm desires to achieve. Adopting the MOLP, an APP is formulated for the firm under study. Later, the simulation model of a firm is created in a discrete-event simulation (DES) software Arena© to evaluate the applicability of the proposed APP. A comparative analysis of the manufacturing performance levels (namely throughput, lead time, and resource utilization) achieved through the implication of an existing production plan and proposed APP is conducted further.

The findings from the study depict that the proposed MOLP-based APP can satisfy the customers' requirement (namely throughput and lead time) and improve the level of resource utilization compared with the firm's existing production plan.

The proposed research facilitates researchers and practitioners to understand the process of developing MOLP-based MPMP APP and analyzing its applicability through simulation technique to be utilized for developing APP at their firm.

An integrated FAHP-MOLP-simulation framework is the novel contribution to the literature on production planning. It can be extended to solve strategic, tactical, and operational problems in different domains like service, healthcare, supply chain, logistics, and project management.